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Dissertations / Theses on the topic 'Optimization and supply chain Management'
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Romero, Morales Dolores. "Optimization problems in supply chain management /." [S.l.] : [s.n.], 2000. http://aleph.unisg.ch/hsgscan/hm00021582.pdf.
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Wike, Carl E. 1948. "Supply chain optimization : formulations and algorithms." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/9763.
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Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 1999.Includes bibliographical references (leaves 103-106).
In this thesis, we develop practical solution methods for a supply chain optimization problem: a multi-echelon, un capacitated, time-expanded network of distribution centers and stores, for which we seek the shipping schedule that minimizes total inventory, backlogging, and shipping costs, assuming deterministic, time-varying demand over a fixed time horizon for a single product. Because of fixed ordering and shipping costs, this concave cost network flow problem is in a class of NP-hard network design problems. We develop mathematical programming formulations, heuristic algorithms, and enhanced algorithms using approximate dynamic programming (ADP). We achieve a strong mixed integer programming (MIP) formulation, and fast, reliable algorithms, which can be extended to problems with multiple products. Beginning with a lot-size based formulation, we strengthen the formulation in steps to develop one which is a variation of a node-arc formulation for the network design problem. In addition, we present a path-flow formulation for the single product case and an enhanced network design formulation for the multiple product case. The basic algorithm we develop uses a dynamic lot-size model with backlogging together with a greedy procedure that emulates inventory pull systems. Four related algorithms perform local searches of the basic algorithm's solution or explore alternative solutions using pricing schemes, including a Lagrangian-based heuristic. We show how approximate dynamic programming can be used to solve this supply chain optimization problem as a dynamic control problem using any of the five algorithms. In addition to improving all the algorithms, the ADP enhancement turns the simplest algorithm into one comparable to the more complex ones. Our computational results illustrate that our enhanced network design formulation almost always produces integral solutions and can be used to solve problems of moderate size (3 distribution centers, 30 stores, 30 periods). Our heuristic methods, particularly those enhanced by ADP methods, produce near optimal solutions for truly large scale problems.
by Carl E. Wike.
S.M.
3
Xu, Shubin, and Shubin Xu. "Essays in Operations and Supply Chain Management." Thesis, University of Oregon, 2012. http://hdl.handle.net/1794/12408.
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This dissertation is based on three essays in operations and supply chain management.
In essay 1, we study an operations scheduling problem in a complex manufacturing system, most notably, semiconductor manufacturing. In particular, we study the scheduling problem of minimizing total weighted tardiness on parallel non-identical batch processing machines. We formulate the (primal) problem as a nonlinear integer programming model. Moreover, we prove that the primal problem can be solved exactly by solving a corresponding dual problem with nonlinear relaxation. Since both the primal and the dual problems are NP-hard, we propose to use genetic algorithms, based on random keys and multiple choice encodings, to heuristically solve them. We found that the genetic algorithms consistently outperform a standard mathematical programming package in terms of solutions and computation times. We also found that for small scale problem instances, the multiple choice genetic algorithm outperforms the random keys genetic algorithm, while for medium and large scale problem instances, the random keys genetic algorithm outperforms the multiple choice genetic algorithm.
In essay 2, we study a monopolist firm offering successive versions of a durable good (e.g., software) that improves over time. The firm decides the time between successive introductions as well as price. In turn, consumers strategically decide whether to purchase or wait for a later version. We model and analyze three alternative strategies for offering successive product versions: the partial-, continuous-, and no-updates policies. We first consider the firm's profit maximizing policy assuming a homogeneous market and subsequently address consumers with heterogeneous product valuations. Our analytic model's simple structure and results highlight the important tradeoff between price and release timing for products with successive versions.
In essay 3, we study the effect of time series structure of customer demand models on the value of information sharing within a supply chain. We contribute to the literature by incorporating a nonlinear demand model based on exponential disturbances, coupled with temporal heteroscedasticity, which captures more complex patterns in the demand process. We examine the conditions under which information sharing is valuable.10000-01-01
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Huang, Wei. "Optimization models for sourcing decisions in supply chain management." [Gainesville, Fla.] : University of Florida, 2004. http://purl.fcla.edu/fcla/etd/UFE0006605.
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Lo, Billy S. (Billy Si Yee). "Inventory optimization in an aerospace supply chain." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/39678.
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Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; in conjunction with the Leaders for Manufacturing Program at MIT, 2007.Includes bibliographical references (p. 66-67).
Strategic inventory management has become a major focus for Honeywell Aerospace as the business unit challenged itself to meeting cost reduction goals while maintaining a high level of service to its customers. This challenge has become particularly important as customers have steered their purchase decisions from focusing only on capability and quality to including cost performance as well. To do so, Honeywell Aerospace's Planning and Asset Management group is undertaking a three-year effort to re-engineer its inventory planning systems with the goal of increasing planner productivity, improving supply chain responsiveness, and reducing overall inventory. This internship forms the building blocks of this strategy by leveraging existing software available in the industry and applying it to Honeywell's supply chain. Through two pilot programs with different supply chain designs, this internship analyzed the cost and benefit of transforming the company's inventory management strategy. In addition, this internship attempts to identify the challenges associated with such an enormous change, compare them with challenges with implementation in other industries in order to prepare management for full implementation across all product lines. These challenges range from leadership buy-in and information readiness to implementation feasibility both within Honeywell manufacturing and its suppliers.
by Billy S. Lo.
S.M.
M.B.A.
6
Ng, Chong Keat. "Inbound supply chain optimization and process improvement." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/81122.
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Thesis (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; and, (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; in conjunction with the Leaders for Global Operations Program at MIT, 2012.Cataloged from PDF version of thesis.
Includes bibliographical references (p. 58).
The primary goal of this project is to evaluate Amazon's inbound supply chain processes and identify improvement opportunities in transportation cost and lead time. Analysis will be focused on defining the current state and evaluating the strengths and weaknesses of the inbound processes. This paper will also include a literature review of the various freight consolidation and vendor coordination strategies in the industry and their impact on cost and lead time. Specific case studies based on actual cost savings programs will be discussed.
by Chong Keat Ng.
M.B.A.
S.M.
7
Hsu, Stephanie K. (Stephanie Karen) 1976. "Supply chain optimization in a retail environment." Thesis, Massachusetts Institute of Technology, 2003. http://hdl.handle.net/1721.1/84354.
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Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2003.Includes bibliographical references (p. 53).
by Stephanie K. Hsu.
S.M.
M.B.A.
8
Henkle, Aimee L. (Aimee Leigh) 1975. "Global supply chain design and optimization methodology." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/34762.
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Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science; in conjunction with the Leaders for Manufacturing Program at MIT, 2004.Includes bibliographical references (p. 72).
The work for this thesis was performed at Honeywell in the Automation and Control Solutions (ACS) division. The project focuses on ACS's manufacturing strategy regarding its global supply chain design, primarily discussing the manufacturing growth opportunities available in emerging regions. Honeywell ACS's current methodology for the development of a long-term manufacturing strategy is based on growth and total cost reduction objectives. In order to comprehend the total cost of the manufacturing strategy, considerations such as inventory, logistics and duties, outsourcing and material sourcing are evaluated. The project also considers a factory's geographical location and ACS's year-by-year implementation plan. An outcome of this Honeywell project and the basis of this thesis is the development of a general supply chain design and optimization methodology that utilizes three analytical tools (Country Selection Framework, Total Cost Model and Implementation Plan Process) that are capable of validating the supply chain design of any company. The analytical tools can be used to verify key strategic supply chain decisions or to create a baseline manufacturing strategy. The following results can be determined using this supply chain design methodology: Determine an appropriate operating region for current or future business needs; Evaluate the feasibility of factory relocation projects by considering all relevant costs; Evaluate the cost implications of the supply chain structure by considering logistics, inventory and material sourcing costs; Understand the impact of outsourcing on the manufacturing strategy; Recommend a year-by-year implementation plan in the case of multiple projects and limited capital resources.
by Aimee L. Henkle.
S.M.
M.B.A.
9
Gunnarsson, Helene. "Supply chain optimization in the forest industry /." Linköping : Department of Mathematics, Linköpings universitet, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8856.
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Karimipour, Hadadan Elham. "Inventory Optimization through Integration of Marketing and Supply Chain Management." Thesis, Högskolan i Gävle, Avdelningen för ekonomi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-21969.
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Purpose: This study aims to find how the integration between marketing and operations can improve demand management in order to have efficient inventory level and avoid excess inventory. Method used: In order to have optimize inventory level and managing demand, integrating business process between marketing, supply planning and inventory management team was considered in this study. Qualitative data from nine interviews among three direct sales cosmetics companies was gathered. Findings: Empirical findings address excess inventory is caused by several issue in the company as poor management of demand forecasting, wide product portfolio, long lead time, the lack of sharing information between the company and its suppliers and ineffective strategy to avoid excess inventory within the company. Regarding to improve forecast accuracy and manage demand, findings indicate the role of marketing in obtaining knowledge about customer insight is not good enough. Practical Implication: It is critical that works and plans from each function be integrated to optimize inventory. In order to support optimize inventory strategy all pertinent departments must continue reviewing meeting with the aim to reach a consensus about the products planning for the both side of demand and operation align with overall strategic goals of the company. Contribution: Empirical data demonstrate the best way for effective implication of demand management occurs when marketing can provide demand information in time, as well as supply chain management can react flexibly to demand changes in time. Moreover, the lack of integration between marketing and supply chain management is a major barrier in optimizing inventory.
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Coughlin, R. Lawrence (Robert Lawrence) 1965. "Optimization and measurement of a world-wide supply chain." Thesis, Massachusetts Institute of Technology, 1998. http://hdl.handle.net/1721.1/9990.
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Thesis (M.S.)--Massachusetts Institute of Technology, Sloan School of Management; and, Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1998.Includes bibliographical references (leaf 81).
by R. Lawrence Coughlin, III.
M.S.
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Zipperer, Damaris R., and Andrew N. Brown. "A generalized framework for optimization with risk." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/112854.
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Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2017.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 51-52).
Supply chains are facing increasingly volatile environments. Traditional optimization solutions provide a baseline understanding for industry applications, but cost-efficient solutions require a more robust approach. In high-tech capital construction projects, the construction of facilities requires complex project schedules, forecast well in advance. These forecasts are used to hire contract workers of varying contract lengths. In this thesis, we develop a risk integration methodology for contract workforce hiring optimization, and explore the capability of generalizing this approach for other supply chain problems. We first create a risk-integrated, optimal solution for workforce hiring that strategically covers areas of high risk density in construction forecasts. We first develop a program to simulate schedule variations based on the associated risk parameters of the scheduled tasks. Using the risk statistics resulting from these simulated schedules, we build new schedule requirements using two different methods. The first method addresses the gap from a daily perspective (bottom-up), while the second method addresses it from an overall schedule perspective (top-down). These new requirements are each overlaid on the input schedule, re-optimized, and excess daily coverage is trimmed. Using both methods, we found that higher levels of risk coverage were achieved at lower costs than the traditional solutions. In the studied case for Intel, a 23% additional risk coverage was generated for equivalent cost. Ultimately, the results show that strategic risk integration can result in a lower final cost, and a generalized framework for risk integration can be applied across many supply chain problems.
by Damaris R. Zipperer and Andrew N. Brown.
M. Eng. in Supply Chain Management
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Romero, Gonzalo (Gonzalo Ignacio Romero Yáñez). "Optimization driven approaches for subsidy allocation and supply chain procurement." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/108210.
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Thesis: Ph. D., Massachusetts Institute of Technology, Sloan School of Management, 2014.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 179-184).
This thesis introduces several new models in operations management, that are motivated by practical settings. It studies these models in an optimization-driven approach, employing mathematical programming techniques to derive important structural and algorithmic insights on the corresponding problems. In the first part of the thesis, we study subsidy allocation problems under budget constraints and endogenous market response, where the central planner's objective is to maximize the market consumption of a good. We first consider co-payment subsidies, that are paid to manufacturing firms per unit sold. We focus on "uniform co-payments", in which each firm receives the same co-payment, regardless of its cost structure, or efficiency. Uniform co-payments are frequently implemented in practice. Therefore, a natural question is whether uniform co-payments are in fact the best that the central planner can do; or, more generally, how do they perform compared to the optimal co-payment allocation? Notably, we first identify relatively general sufficient conditions such that uniform co-payments are optimal, even if the firms are heterogeneous, and if the central planner is uncertain about the market response. We then complement the effectiveness of uniform co-payments, by studying a very relevant setting where they are not optimal. We show that, for any instance of this model, uniform co-payments are guaranteed to induce at least 85% of the optimal market consumption. In summary, uniform co-payments turn out to be surprisingly powerful in maximizing the market consumption of a good. We then consider lump sum subsides, which are an alternative subsidy mechanism also implemented in practice. We show that the problem of optimally allocating lump sum subsidies is NP-hard, and discuss two simple allocation policies that have good performance guarantees. In the second part of the thesis, we introduce a model to incorporate the cost of handling orders at a central distribution center, into the procurement decisions of a company. We show how structural results for this model lead to a practical method to select the best case pack size per SKU in procurement contracts, as well as to serve orders at the distribution center. Furthermore, we test this method on real data from a large utility company, finding significant total cost reductions.
by Gonzalo Romero.
Ph. D.
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Celmins, John M. (John Michael). "Supply chain strategy and optimization in an outsourced environment." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/34836.
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Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering; in conjunction with the Leaders for Manufacturing Program at MIT, 2005.Includes bibliographical references (leaves 77-78).
Sun Microsystem's Network Storage (NWS) Division provides computer network storage hard disk arrays to accompany Sun's core server products. In recent years, all of the incumbent network storage providers, including Sun, have been squeezed by the combination of competitors encroaching on the low-end of the business and the increased commoditization of storage products. As a result, these incumbents are under pressure to reduce costs significantly, and are scrutinizing their supply chain to identify opportunities to improve performance. Most of the production of these storage products is outsourced through either OEM relationships or contract manufacturing, creating numerous challenges for managing the supply chain. This thesis sets forth a framework for improving supply chain performance, and applies it to the Sun's Network Storage group. The supply chain analysis framework used in this thesis suggests improving a supply chain by analyzing six key elements: Metrics, Benchmarking, Inventory Management, Cycle-Time, Design for Supply Chain, and Supply Chain Structure. Metrics were developed to improve supplier delivery. Benchmarking revealed Sun's competitive position.
(cont.) Inventory management was improved with the implementation of a min-max inventory scheme to select products. Cycle-time was investigated via a direct shipment initiative and test time investigations. The upstream component led to product development recommendations. And the supply chain strategy of postponement of customization concept was developed. Key learnings include the relevance of metrics, the difficulty of moving down market, and a greater understanding of the impact product development has on operations. The research for this thesis was conducted during an internship at Sun Microsystems, within the Worldwide Operations group, in affiliation with the Leaders for Manufacturing program at the Massachusetts Institute of Technology.
by John M. Clemens.
S.M.
M.B.A.
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SOUZA, DAYVES PEREIRA FERNANDES DE. "STOCK MANAGEMENT MODELS AND SUPPLY SYSTEM OPTIMIZATION FOR A DRUGSTORE CHAIN." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2007. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=11324@1.
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O varejo brasileiro, tem passado pelo mesmo processo de
concentração de
empresas, assim como, também acontece com vários outros
setores a nível
mundial. A estabilidade econômica e concorrentes cada vez
mais profissionais
forçam as empresas a buscarem a excelência em suas
operações. O investimento
em estoques para este segmento é elevado, pois as empresas
trabalham com uma
grande quantidade de produtos, espalhados entre várias
filiais e centros de
distribuição, preços médios altos e uma grande quantidade
de produtos com giro
baixo. Fatores sazonais e lançamento de novos produtos
alteram a demanda ao
longo do tempo, forçando uma resposta rápida para evitar
perdas de vendas. A
diferença entre o lucro e o prejuízo dos varejistas, pode
estar no ciclo de
gerenciamento dos estoques. Nesta dissertação, são
apresentados os pensamentos
de alguns pesquisadores sobre o tema. Após é descrito as
informações sobre o
mercado e a empresa, em seguida é analisado o sistema de
ressuprimento da rede
de drogarias e com base no referencial teórico e nos
problemas identificados, foi
elaborado uma proposta de gerenciamento e otimização dos
principais indicadores
do sistema de ressuprimento. Os dados foram modelados e os
resultados deste
modelo são demonstrados no final da dissertação.The Brazilian retail market has been facing the same players concentration process, as can be seen in many others sectors around the world. The Brazilian economy stabilization and players with more professionalism, require companies to have the excellence in their operations. The investment in stock is too high for this sector, because there are lot of products, located in many stores, distribution centers, products with a high average costs price and many of them have with a low trn over around the time. Seasonal factors and new products launch, changes the demand across the time and requests a quick response to avoid loses. The difference between loss and profit of the retailers can be found in the supply management cycle. This dissertation shows the thoughts from some researches related to the subject been studied. After, the information about the market and the company are described, follows by the supply chain of the drugstore chain analysis. Based on the theory and the problems identified, an alternative way to manage and optimize the supply system is suggested. The model was tested and the results will be show in the end of the dissertation.
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Luna, Coronado Jaime. "An optimization model for strategic supply chain design under stochastic capacity disruptions." Texas A&M University, 2007. http://hdl.handle.net/1969.1/85844.
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This Record of Study contains the details of an optimization model developed for Shell Oil Co. This model will be used during the strategic design process of a supply chain for a new technology commercialization. Unlike traditional supply chain deterministic optimization, this model incorporates different levels of uncertainty at suppliers' nominal capacity. Because of the presence of uncertainty at the supply stage, the objective of this model is to define the best diversification and safety stock level allocated to each supplier, which minimize the total expected supply chain cost. We propose a Monte Carlo approach for scenario generation, a two-stage non-linear formulation and the Sample Average Approximation (SAA) procedure to solve the problem near optimality. We also propose a simple heuristic procedure to avoid the nonlinearity issue. The sampling and heuristic optimization procedures were implemented in a spreadsheet with a user's interface. The main result of this development is the analysis of the impact of diversification in strategic sourcing decisions, in the presence of stochastic supply disruptions.
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Hassen, Kedir, and Daniel Szucs. "Supply Chain Optimization in the Oil Industry : A Case Study of MOL Hungarian Oil and Gas PLC." Thesis, Internationella Handelshögskolan, Högskolan i Jönköping, IHH, Centre of Logistics and Supply Chain Management, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:hj:diva-18500.
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Abstract Problem discussion: The significance of the oil industry’s impact on the global economy is obvious. Oil supply chain management has to solve a lot of challenges caused by the nature of the supply chain in the oil industry such as complexity, inflexible characteristics, long lead time, limited transportation forms at the different stages in the supply chain, rigid take or pay procurement and limited primary distribution capacity. Other challenges are caused by unforeseen events such as political or economic changes which have an impact on the price of the oil. This thesis seeks to add value by signifying and indicating optimization as a way to address uncertainties and points out a way to utilize resources efficiently in order to gain further development and cost savings in the long term. Finding options for optimization of the oil supply chain is vital because any cost saving means vast amounts of money for the oil companies therefore optimization is at the centre of attention in the oil supply chain management. Purpose: The purpose of this thesis is to investigate supply chain management in the oil industry and find options for optimizing the supply chain in the oil industry by reviewing and analyzing previously written literature on the chosen topic for the research. Method: A single case study was applied in this thesis. The company chosen for the case study is called MOL Hungarian oil and gas PLC and is located in Hungary. To carry out the research, a qualitative research approach was implemented. Primary data was collected through semi structured interviews via telephone and the internet with the company’s staff. In addition to this, secondary data from different sources such as articles and books were used to construct or build the theoretical frame of reference for the thesis. Delimitation: The scope of the thesis is limited to the supply chain management in the oil industry and its optimization. Further narrowing the scope, this thesis gives more attention to the downstream section of the supply chain in the oil industry. Conclusion: Optimization is recognised as main tool for the oil companies to achieve competitive advantage. Analysing MOL Group gives a factual example how optimization works in an oil company and contributes to manage its supply chain efficiently and handle the many uncertainties surrounding the oil industry. It is demonstrated what factors play key role in optimization and how they interact with each other. MOL Group’s solution for optimization builds around a serious planning process, IT solution, marketing and refinery operation triggering and working in synergy with many other factors which cannot be excluded from the optimization process. Due to the excellence of supply chain optimization, MOL Group has a very strong presence and leading position in the East Central European region generating increasing profit margin year by year in last two decades.
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Kostin, Andrey. "Development of advanced mathematical programming methods for supply chain management." Doctoral thesis, Universitat Rovira i Virgili, 2013. http://hdl.handle.net/10803/108957.
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El objetivo es desarrollar una herramienta de apoyo a la toma de decisiones para la planificación estratégica de cadenas de suministro (CS). La tarea consiste en determinar el número, ubicación y capacidad de todos los nodos de la CS, su política de expansión, el transporte y la producción entre todos los nodos de la red. El problema se formula como un modelo de programación lineal entera mixta (MILP) que se resuelve utilizando diferentes herramientas. En primer lugar se desarrolló una estrategia de descomposición para acelerar el proceso de resolución En segundo, se utilizó el algoritmo de aproximación para resolver el problema MILP estocástico. Por último, el modelo multi-objetivo incorpora las soluciones de compromiso entre los aspectos económicos y ambientales. Todas las formulaciones se aplicaron al caso real de la industria de caña de azúcar en Argentina. El objetivo de las herramientas es ayudar a los responsables de planificación estratégica de las infraestructuras para la producción de productos químicos.The aim of this thesis is to provide a decision-support tool for the strategic planning of supply chains (SCs). The task consists of determining the number, location and capacities of all SC facilities, their expansion policy, the transportation links that need to be established, and the production rates and flows of all materials involved in the network. The problem is formulated as a mixed-integer linear programming (MILP) model, which is solved using several mathematical programming tools. First, a decomposition strategy was developed to expedite the solving procedure. Second, the approximation algorithm was utilized to solve the stochastic version of the MILP. Finally, the multi-objective model was developed to incorporate the trade-off between economical and ecological issues. All formulations were applied to a real case based on the Argentinean sugarcane industry. The tools presented are intended to help policy-makers in the strategic planning of infrastructures for chemicals production.
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Rao, Jun M. Eng Massachusetts Institute of Technology. "Improvement on service part supply chain with centralized management and global optimization." Thesis, Massachusetts Institute of Technology, 2006. http://hdl.handle.net/1721.1/38288.
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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2006.Includes bibliographical references (leaf 43).
This project was performed under the supervision of the global supply chain department of InFocus Corp. The company is having high service costs in the Asia Pacific region and desperate to lower the cost in the reverse supply chain and to improve the service level to its customers. In this thesis report, InFocus' current reverse supply chain networks in different business regions were reviewed and detailed analysis was performed for the Asia Pacific region. The results of the analysis showed that the service part supply chain in the Asia Pacific was inefficient and costly due to redundant echelon, insufficient information sharing and lack of centralized management. A shorter and more centralized supply chain was proposed. A comparison was made and various key performance indicators were used to judge the effectiveness of the improvements. The analysis showed that the proposed supply chain has lower costs, lesser safety stock, and higher service levels. Transportation was also shown to be more flexible and cost effective through the proposed replenishment policies. Strategic 3PL partnership and vendor managed inventory (VMI) were also discussed in the later part of the report. Future work can be devoted in these areas to explore the potential of further improvement in the reverse supply chain.
by Jun Rao.
M.Eng.
20
Giacomantonio, Robert. "Multi-echelon inventory optimization in a rapid-response supply chain." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/80995.
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Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; in conjunction with the Leaders for Global Operations Program at MIT, 2013.Cataloged from PDF version of thesis.
Includes bibliographical references (p. 91-92).
The motivation for multi-echelon supply chain management at Nike is to more cost-effectively accommodate customer-facing lead time reduction in the rapid-response replenishment business model. Multi-echelon inventory management, as opposed to a traditional finished-goods only philosophy, provides two clear benefits to a make-to-stock supply chain: first, it increases flexibility through staging calculated work-in-process inventory buffers at critical supply chain links and allowing postponed identification of finished goods; second, inventories held as work-in- process are typically carried at lower cost than finished goods. This thesis details the completion of a project intended to improve Nike's ability to determine optimal inventory levels by balancing cost and service level tradeoffs in a multi-echelon-enabled environment. The goal is to develop an inventory modeling methodology for Nike's supply chain data architecture specifically to evaluate the hypothesis that multi-echelon inventory management will present only limited opportunity for cost reduction in offshore, long lead time make-to-stock supply chains. To directly asses the hypothesis, Llamasoft's Supply Chain Guru optimization software will be deployed to create an inventory optimization model for a specific family of apparel products sold as part of Nike's replenishment offering in North America. The modeling results confirm the hypothesis that multi-echelon inventory management offers little value to the current offshore supply chain. Sensitivity and scenario analysis is utilized to identify significant inventory drivers, areas for substantial improvement, and profitable opportunities for multi-echelon inventory management.
by Robert Giacomantonio.
S.M.
M.B.A.
21
Helberg, Mark Nicholas. "Location-Allocation Optimization of Supply Chain Distribution Networks: A Case Study." BYU ScholarsArchive, 2013. https://scholarsarchive.byu.edu/etd/3778.
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The location of distribution centers is an important strategic decision in supply chain design, particularly as it relates to service quality, productivity, and profitability of the firm. There has been extensive research performed on distribution location models which require the use of complex algorithms and assumptions that make use of these models difficult in practice for small and medium enterprises (SMEs) that have limited capital and resources. Studies have also failed to capture and quantify potential business results of using more sophisticated methods. In this study, a deterministic and static location-allocation model is designed using a prototype software tool. The tool is a collection of Excel/VBA programs formulated as a mixed integer programming (MIP) model. Research was done in conjunction with a personal care products company that provided a unique opportunity to evaluate the manual methods typically used in SMEs with the results of the software tool and the potential business impact. Both quantitative data, including customer locations and order information, as well as qualitative data were collected from the company. A total of five models were simulated using the prototype software tool, including one model of the current supply chain for use as a base comparison, and four future-state models of potential distribution center (DC) location scenarios. The objective in each of these models was to minimize transportation costs while maintaining the desired service fulfillment levels. The use of the prototype software tool resulted in a more optimal supply chain solution. The optimized DC location resulted in a network design with a 6.5% reduction in transportation costs from the base model, and a 0.8% reduction in transportation costs from a location previously chosen by the company. The results also provided insight into considering weighted shipping volume in location analysis as it can serve as a magnifier of business impact and rapid diminishing returns when shipping product below an average of 10 pounds. The use of an optimization tool was shown to mitigate many issues SMEs encounter in attempting to synthesize multiple variables in the DC location problem.
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Yoon, Justin J. "The traveling salesman problem with multiple drones : an optimization model for last-mile delivery." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/117930.
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Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2018.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 47-49).
With the increasingly competitive landscape of e-commerce and omni-channel delivery execution, the last mile has emerged as a critical source of opportunity for cost efficiency. Unmanned aerial vehicles (UAVs) have historically been utilized for military applications, but they are quickly gaining traction as a viable option for driving improvements in commercial last-mile operations. Although extensive literature currently exists on vehicle routing problems, research integrating drones as a supplement to these routing problems is scarce. This thesis explores the feasibility of deploying drones to the last mile, by modeling the cost of serving customers with one truck and multiple drones in the context of the traveling salesman problem. The model is constructed with mixed integer linear programming (MILP) optimization and assessed with a sensitivity analysis of several key parameters. We find significant median cost savings over TSP of 30 percent in the base case, and that these effects on savings can diminish to a median 4 percent in the worst case while surging up to 55 percent in the best case.
by Justin J. Yoon.
M. Eng. in Supply Chain Management
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Elahi, Behin. "Integrated Optimization Models and Strategies for Green Supply Chain Planning." University of Toledo / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1467266039.
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Stockheim, Tim. "Supply network optimization : coordination based on economic scheduling, negotiation and trust /." Norderstedt : Books on Demand, 2006. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=015014948&line_number=0002&func_code=DB_RECORDS&service_type=MEDIA.
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Hultman, Gustav. "DISTRIBUTION NETWORK DESIGN : Optimization & simulation of an international supply chain." Thesis, Umeå universitet, Institutionen för matematik och matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-171754.
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Höganäs AB's current distribution network for iron powder in the Asia Pacific (APAC) region is subject to high costs incurred by large inventories and high cost of capital. As a result of increasing demand and service level requirements from customers, inventories have steadily increased. Keeping a high inventory level has enabled high service levels irrespective of supply disruptions or changes in demand. It is important that the distribution network incorporates a balance between robustness and cost efficiency and not only focuses on one of these aspects. The purpose of this project is to provide Höganäs AB with scientific data on how the distribution network can be improved in terms of lowering the total cost of warehousing and distribution while maintaining or improving customer service. There are several goals for this project. The first goal is to optimize the flow of material in the distribution network given empirical data of customer demand. The intended model is a linear program. The linear program will solve a multi echelon, period, product, location and transportation mode instance of the distribution network design problem. The second goal is to test the robustness of the optimal solutions resulting from the linear program by stochastic simulation. The simulations utilize the optimal network designs generated by the linear program and is done for a set of possible scenarios where key parameters are changed. By adjusting key parameters and measuring the effect on cost and service level, the goal is to evaluate the robustness of each configuration. By keeping the existing nodes of the distribution network and changing the flow of material and distribution strategy, lower inventories can be maintained and service level kept high regardless of demand growth and supply disruption. The optimal distribution network design is one from the linear program, configured with a 14 day inventory level and 10 day reorder point for warehouses. The optimal design shows that distribution is made more robust and efficient by allowing for distribution between warehouses or supplying customers normally affiliated with other warehouses. It also suggests that a central redistribution warehouse is a possible improvement to the current network design.Höganäs AB's nuvarande distributionsnätverket for järnpulver i Asien-Stillahavsregionen (APAC) är kostsamt till följd av höga lagernivåer och kapitalkostnader. Ökande efterfrågan och krav på hög servicenivå har inneburit en stadig ökning av lagernivåerna, vilket möjliggjort för företaget att upprätthålla servicenivån oberoende av störningar i leveranskedjan eller förändringar i efterfrågan. Det är viktigt att distributionsnätverket är balanserat avseende stabilitet och kostnadseffektivitet och inte endast optimeras avseende en av faktorerna. Syftet med projektet är förse Höganäs AB vetenskapligt understödd information om hur den totala kostnaden för distributionsnätverket kan sänkas samtidigt som kundservicen upprätthålls eller förbättras. Det finns flera mål för projektet. Det första målet är att optimera materialflödet i distributionsnätverket givet empiriska data över efterfrågan. Den avsedda modellen är ett linjärprogram som löser en instans av distributionsnätverkverksdesign-problemet med multipla lager, perioder, produkter, lokaliseringar och transportsätt. Det andra målet är att utvärdera stabiliteten hos de optimala lösningar som härrör från linjärprogrammet genom stokastisk simulering. Simuleringarna använder de optimala nätverksdesigner som genereras av det linjärprogrammet och genomförs för en uppsättning möjliga scenarier där nyckelparametrar ändras. Genom att justera nyckelparametrar och mäta effekten på kostnad och servicenivå är målet att utvärdera stabiliteten för varje konfiguration. Genom att behålla de befintliga noderna i distributionsnätverket och ändra materialflödet samt distributionsstrategin kan lägre lagernivåer uppnås och servicenivån hålls hög oavsett förändrad efterfrågan och störningar i leveranskedjan. Den optimala distributionsnätverkverksdesignen är en lösning från linjärprogrammet konfigurerat med 14 dagars lagernivå och 10 dagars beställningspunkt. Den optimala designen visar att distributionen görs mer stabil och effektiv genom att tillåta leveranser mellan lagerpunkterna eller att försörja kunder från andra lagerpunkter än de normalt försörjs från. Resultatet påvisar också att en strategiskt placerad omlastningscentral kan förbättra det nuvarande distributionsnätverket.
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El, KHOURY Hiba. "Introduction of New Products in the Supply Chain : Optimization and Management of Risks." Phd thesis, HEC, 2012. http://pastel.archives-ouvertes.fr/pastel-00708801.
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Shorter product life cycles and rapid product obsolescence provide increasing incentives to introduce newproducts to markets more quickly. As a consequence of rapidly changing market conditions, firms focus onimproving their new product development processes to reap the benefits of early market entry. Researchershave analyzed market entry, but have seldom provided quantitative approaches for the product rolloverproblem. This research builds upon the literature by using established optimization methods to examine howfirms can minimize their net loss during the rollover process. Specifically, our work explicitly optimizes thetiming of removal of old products and introduction of new products, the optimal strategy, and the magnitudeof net losses when the market entry approval date of a new product is unknown. In the first paper, we use theconditional value at risk to optimize the net loss and investigate the effect of risk perception of the manageron the rollover process. We compare it to the minimization of the classical expected net loss. We deriveconditions for optimality and unique closed-form solutions for single and dual rollover cases. In the secondpaper, we investigate the rollover problem, but for a time-dependent demand rate for the second producttrying to approximate the Bass Model. Finally, in the third paper, we apply the data-driven optimizationapproach to the product rollover problem where the probability distribution of the approval date is unknown.We rather have historical observations of approval dates. We develop the optimal times of rollover and showthe superiority of the data-driven method over the conditional value at risk in case where it is difficult to guessthe real probability distribution
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El-Khoury, Hiba. "Introduction of New Products in the Supply Chain : Optimization and Management of Risks." Thesis, Jouy-en Josas, HEC, 2012. http://www.theses.fr/2012EHEC0001/document.
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Les consommateurs d’aujourd’hui ont des goûts très variés et cherchent les produits les plus récents. Avec l’accélération technologique, les cycles de vie des produits se sont raccourcis et donc, de nouveaux produits doivent être introduits au marché plus souvent et progressivement, les anciens doivent y être retirés. L’introduction d’un nouveau produit est une source de croissance et d’avantage concurrentiel. Les directeurs du Marketing et Supply Chain se sont confrontés à la question de savoir comment gérer avec succès le remplacement de leurs produits et d’optimiser les coûts de la chaîne d’approvisionnement associée. Dans une situation idéale, la procédure de rollover est efficace et claire: l’ancien produit est vendu jusqu’à une date prévue où un nouveau produit est introduit. Dans la vie réelle, la situation est moins favorable. Le but de notre travail est d’analyser et de caractériser la politique optimale du rollover avec une date de disponibilitéstochastique pour l’introduction du nouveau produit sur le marché. Pour résoudre le problème d’optimisation,nous utilisons dans notre premier article deux mesures de minimisation: le coût moyen et le coût de la valeurconditionnelle à risque. On obtient des solutions en forme explicite pour les politiques optimales. En outre, nous caractérisons l’influence des paramètres de coûts sur la structure de la politique optimale. Dans cet esprit, nous analysons aussi le comportement de la politique de rollover optimale dans des contextes différents. Dans notre deuxième article, nous examinons le même problème mais avec une demande constante pour le premier produit et une demande linéaire au début puis constante pour le deuxième. Ce modèle est inspiré par la demande de Bass. Dans notre troisième article, la date de disponibilité du nouveau produit existe mais elle est inconnue. La seule information disponible est un ensemble historique d’échantillons qui sont tirés de la vraie distribution. Nous résoudrons le problème avec l’approche data drivenet nous obtenons des formulations tractables. Nous développons aussi des bornes sur le nombre d’échantillons nécessaires pour garantir qu’avec une forte probabilité, le coût n’est pas très loin du vrai coût optimalShorter product life cycles and rapid product obsolescence provide increasing incentives to introduce newproducts to markets more quickly. As a consequence of rapidly changing market conditions, firms focus onimproving their new product development processes to reap the benefits of early market entry. Researchershave analyzed market entry, but have seldom provided quantitative approaches for the product rolloverproblem. This research builds upon the literature by using established optimization methods to examine howfirms can minimize their net loss during the rollover process. Specifically, our work explicitly optimizes thetiming of removal of old products and introduction of new products, the optimal strategy, and the magnitudeof net losses when the market entry approval date of a new product is unknown. In the first paper, we use theconditional value at risk to optimize the net loss and investigate the effect of risk perception of the manageron the rollover process. We compare it to the minimization of the classical expected net loss. We deriveconditions for optimality and unique closed-form solutions for single and dual rollover cases. In the secondpaper, we investigate the rollover problem, but for a time-dependent demand rate for the second producttrying to approximate the Bass Model. Finally, in the third paper, we apply the data-driven optimizationapproach to the product rollover problem where the probability distribution of the approval date is unknown.We rather have historical observations of approval dates. We develop the optimal times of rollover and showthe superiority of the data-driven method over the conditional value at risk in case where it is difficult to guessthe real probability distribution
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Liu, Mingli. "Supply Chain Management in Humanitarian Aid and Disaster Relief." Thesis, Université d'Ottawa / University of Ottawa, 2014. http://hdl.handle.net/10393/31572.
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Humanitarian aid and disaster relief are delivered in times of crises or natural disasters, such as after a conflict or in response to a hurricane, typhoon, or tsunami. Different from regular aid programs, aid and relief are provided to deal with emergency and immediate local areas, and to shelter affected people and refugees impacted by sudden traumatic events. There is evidence that natural and man-made disasters are increasing in numbers all around the world, affecting hundreds of millions of people every year. In spite of this fact, only in recent years – beginning in 2005 – has management of the supply chain of resources and materials for humanitarian aid and disaster relief been a topic of interest for researchers. Consequently, the academic literature in this field is comparatively new and still sparse, indicating a requirement for more academic studies. As a key part of the C-Change International Community-University Research Alliance (ICURA) project for managing adaptation to environmental change in coastal communities of Canada and the Caribbean, this thesis develops a framework and analytical model for domestic supply chain management in humanitarian aid and disaster relief in the event of severe storm and flooding in the Canadian C-Change community of Charlottetown, Prince Edward Island. In particular, the focus includes quantitative modeling of two specific aspects during the preparedness phase for emergency management: (1) inventory prepositioning and (2) transportation planning. In addition, this thesis proposes and analyses the characteristics of an effective supply chain management framework in practice to assist Canadian coastal communities in improving their preparation and performance in disaster relief efforts. The results indicate Charlottetown system effectiveness and decreased time to assist affected people are improved by distributing central emergency supply among more than one base station.
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Gentiletti, Andrea. "Design and optimization of global distribution supply chain at McCain Foods." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/73383.
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Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; in conjunction with the Leaders for Global Operations Program at MIT, 2012.Cataloged from PDF version of thesis. Vita.
Includes bibliographical references (p. 76-77).
Network design has been successfully used by numerous organizations to achieve supply chain excellence through cost effectiveness and superior utilization of resources. This thesis addresses how network optimization methods can be used to provide guidance in the process of creating a company's global supply chain strategy. In order to demonstrate that this approach can be a source of considerable value for an organization, we collaborated for a period of six and a half months with McCain Foods in the creation of their supply chain strategy plan. In the past McCain has managed its capacity and distribution from a regional perspective. While this method has historically produced good results, the size of the company and the challenges ahead justify now a more global approach. To fully leverage McCain's global scale, we conducted a comprehensive study of the supply chain, analyzing possible scenarios and highlights optimal strategies for future growth plans. For this purpose, we created a global supply chain model using LogicNet Plus, representing the movement of finished products from all French fry plants to all markets. From the analysis of the model, recommendations have been produced for McCain's senior leaders and board, and used in the definition of the 5-year strategic plan. To comply with the tight deadlines of the high-level decision-making process of the organization, the model uses highly aggregated and easily available data, yet it can represent reality with sufficient accuracy. The results of the study clearly show how this kind of analysis is able to provide significant input for the definition of a supply chain strategy, and to highlight opportunities for substantial cost savings in a global supply chain network.
by Andrea Gentiletti.
S.M.
M.B.A.
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Chen, Stephanie Hsuan-Chia, and Eunji Han. "Gaining an operational edge : piece-picking process optimization." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/107522.
Full textAbstract:
Thesis: M. Eng. in Logistics, Massachusetts Institute of Technology, Supply Chain Management Program, 2016.Cataloged from PDF version of thesis.
Includes bibliographical references (pages 66-67).
Order-picking is an integral operation in warehouses and distribution centers (DC), consuming considerable operating resources and expenses. Numerous studies have attempted to optimize the efficiency and reduce the cost of order-picking. In working with a partner company, this thesis evaluates a proposed mechanism for piece-picking that would achieve this end. The company has a shelf-pack number for each SKU, whereby the SKU must be piece-picked in a quantity that is a multiple of the number. The company has proposed to change this number from 1 to 2 to raise the number of units per pick and reduce the number of picks needed for a SKU. In this thesis, simulation is performed on the company's shipment data from DC to store to reveal the merits and demerits of this scheme. SKUs are segmented into different groups based on their suitability for this scheme as a means of mitigating the negative repercussions of the proposal. The scheme can reduce the number of picks and related costs needed, but it causes a shift of inventory from DC to store, thus creating an increase in store inventory. However, SKUs can be allotted into groups suitable or unsuitable for the scheme depending on the amount of savings generated for a given amount of impact on store inventory. The scheme's benefits and impact on store inventory are thoroughly examined, and their implications on DC inventory are also discussed. This thesis offers a novel perspective into piece-picking optimization, and it finds the proposed scheme viable, simple, and flexible.
by Stephanie Hsuan-Chia Chen and Eunji Han.
M. Eng. in Logistics
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Wildi, Philip-Markus. "The Weighted Cash Conversion Cycle in Networks Potential for WACC-Optimization /." St. Gallen, 2008. http://www.biblio.unisg.ch/org/biblio/edoc.nsf/wwwDisplayIdentifier/01655315002/$FILE/01655315002.pdf.
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Toriello, Alejandro. "Time decomposition of multi-period supply chain models." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/42704.
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Many supply chain problems involve discrete decisions in a dynamic environment. The inventory routing problem is an example that combines the dynamic control of inventory at various facilities in a supply chain with the discrete routing decisions of a fleet of vehicles that moves product between the facilities.
We study these problems modeled as mixed-integer programs and propose a time decomposition based on approximate inventory valuation. We generate the approximate value function with an algorithm that combines data fitting, discrete optimization and dynamic programming methodology. Our framework allows the user to specify a class of piecewise linear, concave functions from which the algorithm chooses the value function. The use of piecewise linear concave functions is motivated by intuition, theory and practice. Intuitively, concavity reflects the notion that inventory is marginally more valuable the closer one is to a stock-out. Theoretically, piecewise linear concave functions have certain structural properties that also hold for finite mixed-integer program value functions. (Whether the same properties hold in the infinite case is an open question, to our knowledge.) Practically, piecewise linear concave functions are easily embedded in the objective function of a maximization mixed-integer or linear program, with only a few additional auxiliary continuous variables. We evaluate the solutions generated by our value functions in a case study using maritime inventory routing instances inspired by the petrochemical industry.
The thesis also includes two other contributions. First, we review various data fitting optimization models related to piecewise linear concave functions, and introduce new mixed-integer programming formulations for some cases. The formulations may be of independent interest, with applications in engineering, mixed-integer non-linear programming, and other areas. Second, we study a discounted, infinite-horizon version of the canonical single-item lot-sizing problem and characterize its value function, proving that it inherits all properties of interest from its finite counterpart. We then compare its optimal policies to our algorithm's solutions as a proof of concept.
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Pujari, Nikhil Ajay. "Integrated Supply Chain Optimization Model Using Mathematical Programming and Continuous Approximation." Ohio University / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1132114913.
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Chou, David (David Hancheng). "Creating a corporate strategy for utilizing supply chain simulation, optimization and visualization." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/90764.
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Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2014. In conjunction with the Leaders for Global Operations Program at MIT.Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2014. In conjunction with the Leaders for Global Operations Program at MIT.
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Cataloged from PDF version of thesis.
Includes bibliographical references (page 46).
Computer based supply chain simulation, optimization, and visualization capability have changed significantly in the past 45 years, expanding capability in lockstep with increases in computational power. The increase in accessibility of relatively cheap and powerful hardware has led to the development of a multitude of supply chain simulation, optimization, and visualization programs catered towards reducing corporate supply chain costs. Some of these programs are commercial business to business offerings, while a significant set are developed internally within the corporation. Expertise in this field is increasingly seen as an area of competitive advantage for modern goods based corporations. However, the danger lies in executing decisions based upon inaccurate simulation results, often meaning millions of dollars lost in waste rather than the desired savings. This thesis aims to identify the needs of a corporation regarding supply chain simulation, optimization, and visualization - particularly how a company may categorize offerings within this field - how these programs may fit within the organizational context of a company, and how to ensure correct utilization of a set of supply chain programs. Supply chain is very well understood, but little focus has been placed on correctly utilizing these programs to support success for a company's goal of becoming operationally efficient. A current state analysis of a major U.S. manufacturing company, Caterpillar, Inc., was conducted and a new framework was applied to understand Caterpillar's usage of supply chain programs. This thesis utilizes findings from Caterpillar as a sample case to reinforce research. An overall strategy is developed based on research at Caterpillar, and supports the creation of a group of internal experts disassociated from specific supply chain specialties, such as procurement or logistics, in order to ensure global efficiency. A generic strategy is presented for any corporation utilizing computer based supply chain simulation, optimization, and visualization.
by David Chou.
M.B.A.
S.M.
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Luo, Kai. "Analysis and optimization of single and dual sourcing decisions in supply chain." Thesis, Jouy-en Josas, HEC, 2011. http://www.theses.fr/2011EHEC0010/document.
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L'objectif de cette recherche est de développer des modèles aussi bien conceptuels, analytiques et managériaux en analysant un maillon de la supply chain, à savoir la relation entre un distributeur et deux fournisseurs opérant dans un environnement incertain. Dans la première partie de la thèse, nous considérons un seul produit, plutôt haut de gamme et/ou périssable, et nous faisons l’analyse sur un horizon d’une période. Dans ce cas précis, les caractéristiques unitaires du produit sont toutes non linéaires, à savoir : le prix, le coût de production, le coût de rupture, le coût de reprise. La demande est supposée être une variable aléatoire. Dans la deuxième partie de la thèse, nous nous inspirons des pratiques de firmes internationales qui s’approvisionnent, pour une partie de leur offre, dans des pays à bas coûts. Nous développons plusieurs modèles mais dont la structure de base est similaire, à savoir : deux produits (un haut gamme acheté localement et l’autre bas de gamme acheté dans les pays à bas coûts), un horizon de trois périodes, deux fournisseurs à capacité de production limitée et un distributeur ayant des capacités de stockage limitées. Une panoplie de résultats théoriques, numériques ainsi que des insights sont présentés.Les modèles développés peuvent être utilisés comme des outils d’aide { la prise de décision dans les environnements décrits dans cette thèseThe objective of this research is to develop conceptual, analytical, and managerial models and insights by analyzing a portion of the supply chain made up of a retailer dealing with two suppliers in an uncertain environment. In the first part of this thesis, we consider a single high-end (or perishable) product, single period, variable unit price, variable unit production cost, variable unit shortage cost, variable unit salvagevalue, stochastic demand problem. In a second part of the thesis, we consider settings inspired by the case of large international companies sourcing some of their products from low cost countries. This structure is as follows: two products (one sourced locally and the other sourced abroad), a three-period, two-stages, two capacitated suppliers, and a single capacitated retailer. Both analytical and numerical results are provided. Important theoretical results and insights are developed for these types of settings. These models can be used as decision-making aid tools in such environments
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Riechel, Patrick. "A phased approach to distribution network optimization given incremental supply chain change." Thesis, Massachusetts Institute of Technology, 2012. http://hdl.handle.net/1721.1/73394.
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Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; in conjunction with the Leaders for Global Operations Program at MIT, 2012.Cataloged from PDF version of thesis.
Includes bibliographical references (p. 59-60).
This thesis addresses the question of how to optimize a distribution network when the supply chain has undergone an incremental change. A case study is presented for Company A, a major global biotechnology company that recently acquired a new manufacturing facility in Ireland. Company A already has international operations throughout Europe and the rest of the world through its network of 3rd party logistics providers, wholesalers, and distributors, as well as its own Benelux-based international distribution center. It now seeks to optimize its current network by taking into consideration the possibility of distributing product directly out of Ireland and by potentially outsourcing some of the distribution currently sourced from its Benelux facility. The thesis uses a phased approach to optimizing the network in order to tackle the common enterprise challenges of 1) building consensus around the solution and 2) simultaneously learning about the problem while attempting to solve it in order to meet a compressed project schedule. Through a number of simplifications, the thesis reduces the problem scope to a level that both enables the use of this phased approach and provides for a less-complex and less time-intense analysis manageable within the given time frame. The unique characteristics of the biotechnology industry drive the analysis to closely study direct effects of and potential risks to availability and lead-time of the various distribution options while trading off distribution, packaging, inventory, and capital expenditure costs. The recommendations resulting from the analysis described in this thesis are used to inform Company A's future distribution strategy regarding additional warehousing capacities, the continued use of the Benelux facility, as well as potential strategic partnerships with 3rd party logistics service providers.
by Patrick Riechel.
S.M.
M.B.A.
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Baumgartner, Kerstin. "Optimization approaches for the design of realistic supply chains examples from the chemical industry." Köln Kölner Wiss.-Verl, 2009. http://d-nb.info/999573306/04.
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Nie, Tengfei. "Operations optimization and contracting coordination for behavioral supply chain with typical social preferences." Thesis, Châtenay-Malabry, Ecole centrale de Paris, 2015. http://www.theses.fr/2015ECAP0009/document.
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Cette thèse étudie l’incorporation des préférences sociales typiques, telles que le souci de justice et la réciprocité, dans la chaîne logistique. Les impacts de ces préférences sociales sur la prise de décisions dans la chaîne logistique, sur l’efficacité et la coordination du canal de distribution sont étudiés. Plus spécifiquement, la thèse se focalise sur trois questions essentielles ci-dessous : 1. Qu’est-ce qui différencie un canal conventionnel d’un canal comportemental qui prend en compte la justice et/ou la réciprocité par exemple ? 2. Comment ces facteurs comportementaux influencent-ils la prise de décisions du fournisseur et du distributeur dans la chaîne logistique ? 3. Quels effets ont ces préférences sociales sur la coordination du canal de distribution et sur son efficacité ? Afin de répondre à ces questions, nous développons deux modèles d’opérations comportementales. Nous construisons d’abord un modèle de vendeur de journaux pour une chaîne logistique dyadique avec prise en compte de justice dans un processus de négociation de Nash. Dans ce modèle, un fournisseur joue un jeu de Stackelberg avec un distributeur qui doit faire face à une demande aléatoire. La solution de Nash est utilisèe comme référence de justice pour formellement décrire un compromis perçu comme juste, ce qui constitue une nouvelle manière de traiter la justice dans une chaîne logistique. Ensuite nous étudions un canal de distribution similaire mais où le fournisseur et le distributeur ont une préférence pour la réciprocité et la demande est supposée déterministe. Dans ce modèle, l’impact de l’intention dans une chaîne logistique est étudié pour la première fois. Des analyses approfondies de ces modèles comportementaux nous permettent de tirer des aperçus managériaux intéressants,comme par exemple le fait que le souci de justice joue un rôle important sur la difficulté de coordonner un canal de distribution. Nous avons démontré qu’un canal dyadique avec prise en compte de réciprocité peut être coordonné en utilisant un prix de gros constant, ce qui signifie que le problème de double marginalisation ne se pose pas nécessairement tout le tempsThis thesis studies how to incorporate typical social preferences, such as fairness concerns and reciprocity, into the context of supply chain. The impacts of theses social preferences on the supply chain’s decisions, channel efficiency and coordination are investigated. Specifically, it focuses on three important questions as follows: 1, what are the differences between the conventional channel and the behavioral channel (e.g., fairness-concerned channel and reciprocal channel)? 2, how do these behavioral factors influence the decisions of the supplier and the retailer in the supply chain? 3, what effects have these social preferences on the coordination of the channel and its efficiency? In order to answer these questions, two models of behavioral operations are formulated. A newsvendor model for a dyadic supply chain with Nash bargaining fairness concerns is built first. In this model, a supplier plays Stackelberg game with a retailer who faces stochastic demand. Nash bargaining solution is used as fairness reference to formally depict perceptively fair compromise, which is a new perspective to study fairness concerns in a supply chain. Then a similar dyadic channel in which a retailer and/or a supplier have a preference for reciprocity is investigated, but the retailer is facing deterministic demand. In this model, the impact of intention is studied within the context of supply chain for the first time. Some interesting and valuable managerial insights are drawn by analyzing the two behavioral models. For example, fairness concern does have great impact on the difficulty of coordinating a channel. In addition, the dyadic channel with reciprocity can be coordinated by using a constant wholesale price, which implies that the problem of double marginalization is not necessary to be present all the time
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Li, Bo. "Supply Chain Inventory Management with Multiple Types of Customers: Motivated by Chinese Pharmaceutical Supply Chains among Others." University of Toledo / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1371136834.
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Scholz, Johannes [Verfasser]. "Real-Time Spatial Optimization : Based on the Application in Wood Supply Chain Management / Johannes Scholz." München : GRIN Verlag GmbH, 2011. http://d-nb.info/1065875118/34.
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Gaillard, de Saint Germain Etienne. "Arbitrer coût et flexibilité dans la Supply Chain." Thesis, Paris Est, 2018. http://www.theses.fr/2018PESC1113/document.
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Cette thèse développe des méthodes d'optimisation pour la gestion de la Supply Chain et a pour thème central la flexibilité définie comme la capacité à fournir un service ou un produit au consommateur dans un environnement incertain. La recherche a été menée dans le cadre d'un partenariat entre Argon Consulting, une société indépendante de conseil en Supply Chain et l'École des Ponts ParisTech. Dans cette thèse, nous développons trois sujets rencontrés par Argon Consulting et ses clients et qui correspondent à trois différents niveaux de décision (long terme, moyen terme et court terme).Lorsque les entreprises élargissent leur portefeuille de produits, elles doivent décider dans quelles usines produire chaque article. Il s'agit d'une décision à long terme, car une fois qu'elle est prise, elle ne peut être facilement modifiée. Plus qu'un problème d'affectation où un article est produit par une seule usine, ce problème consiste à décider si certains articles doivent être produits par plusieurs usines et par lesquelles. Cette interrogation est motivée par la grande incertitude de la demande. En effet, pour satisfaire la demande, l'affectation doit pouvoir équilibrer la charge de travail entre les usines. Nous appelons ce problème le multi-sourcing de la production. Comme il ne s'agit pas d'un problème récurrent, il est essentiel de tenir compte du risque au moment de décider le niveau de multi-sourcing. Nous proposons un modèle générique qui inclut les contraintes techniques du problème et une contrainte d'aversion au risque basée sur des mesures de risque issues de la théorie financière. Nous développons un algorithme et une heuristique basés sur les outils standards de la Recherche Opérationnelle et de l'Optimisation Stochastique pour résoudre le problème du multi-sourcing et nous testons leur efficacité sur des données réelles.Avant de planifier la production, certains indicateurs macroscopiques doivent être décidés à horizon moyen terme tels la quantité de matières premières à commander ou la taille des lots produits. Certaines entreprises utilisent des modèles de stock en temps continu, mais ces modèles reposent souvent sur un compromis entre les coûts de stock et les coûts de lancement. Ces derniers sont des coûts fixes payés au lancement de la production et sont difficiles à estimer en pratique. En revanche, à horizon moyen terme, la flexibilité des moyens de production est déjà fixée et les entreprises estiment facilement le nombre maximal de lancements. Poussés par cette observation, nous proposons des extensions de certains modèles classiques de stock en temps continu, sans coût de lancement et avec une limite sur le nombre d'installations. Nous avons utilisé les outils standard de l'Optimisation Continue pour calculer les indicateurs macroscopiques optimaux.Enfin, la planification de la production est une décision à court terme qui consiste à décider quels articles doivent être produits par la ligne de production pendant la période en cours. Ce problème appartient à la classe bien étudiée des problèmes de Lot-Sizing. Comme pour les décisions à moyen terme, ces problèmes reposent souvent sur un compromis entre les coûts de stock et les coûts de lancement. Fondant notre modèle sur ces considérations industrielles, nous gardons le même point de vue (aucun coût de lancement et une borne supérieure sur le nombre de lancement) et proposons un nouveau modèle.Bien qu'il s'agisse de décisions à court terme, les décisions de production doivent tenir compte de la demande future, qui demeure incertaine. Nous résolvons notre problème de planification de la production à l'aide d'outils standard de Recherche Opérationnelle et d'Optimisation Stochastique, nous testons l'efficacité sur des données réelles et nous la comparons aux heuristiques utilisées par les clients d'Argon ConsultingThis thesis develops optimization methods for Supply Chain Management and is focused on the flexibility defined as the ability to deliver a service or a product to a costumer in an uncertain environment. The research was conducted throughout a partnership between Argon Consulting, which is an independent consulting firm in Supply Chain Operations and the École des Ponts ParisTech. In this thesis, we explore three topics that are encountered by Argon Consulting and its clients and that correspond to three different levels of decision (long-term, mid-term and short-term).When companies expand their product portfolio, they must decide in which plants to produce each item. This is a long-term decision since once it is decided, it cannot be easily changed. More than a assignment problem where one item is produced by a single plant, this problem consists in deciding if some items should be produced on several plants and by which plants. This is motivated by a highly uncertain demand. So, in order to satisfy the demand, the assignment must be able to balance the workload between plants. We call this problem the multi-sourcing of production. Since it is not a repeated problem, it is essential to take into account the risk when making the multi-sourcing decision. We propose a generic model that includes the technical constraints of the assignment and a risk-averse constraint based on risk measures from financial theory. We develop an algorithm and a heuristic based on standard tools from Operations Research and Stochastic Optimization to solve the multi-sourcing problem and we test their efficiency on real datasets.Before planning the production, some macroscopic indicators must be decided at mid-term level such as the quantity of raw materials to order or the size of produced lots. Continuous-time inventory models are used by some companies but these models often rely on a trade-off between holding costs and setups costs. These latters are fixed costs paid when production is launched and are hard to estimate in practice. On the other hand, at mid-term level, flexibility of the means of production is already fixed and companies easily estimate the maximal number of setups. Motivated by this observation, we propose extensions of some classical continuous-time inventory models with no setup costs and with a bound on the number of setups. We used standard tools from Continuous Optimization to compute the optimal macroscopic indicators.Finally, planning the production is a short-term decision consisting in deciding which items must be produced by the assembly line during the current period. This problem belongs to the well-studied class of Lot-Sizing Problems. As for mid-term decisions, these problems often rely on a trade-off between holding and setup costs. Basing our model on industrial considerations, we keep the same point of view (no setup cost and a bound on the number of setups) and propose a new model. Although these are short-term decisions, production decisions must take future demand into account, which remains uncertain. We solve our production planning problem using standard tools from Operations Research and Stochastic Optimization, test the efficiency on real datasets, and compare it to heuristics used by Argon Consulting's clients
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Urkiel, Brian A. (Brian Alexander) 1971. "The analysis and optimization of the Alcoa Mill Products supply chain for European customers." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/34702.
Full textAbstract:
Thesis (S.M.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Civil and Environmental Engineering; in conjunction with the Leaders for Manufacturing Program, Massachusetts Institute of Technology, 2000.Also available online at the MIT Theses Online homepage
Includes bibliographical references (p. 100-101).
This thesis examines the challenges of managing a global supply chain in a large, well-established organization and outlines certain techniques that can be utilized to achieve more effective supply chain management. The research was conducted at Davenport Works, which is part of the Alcoa Mill Products (AMP) Business Unit, and examined the business unit's global supply chain with its European customers. The presence of inventory can hide many of the root cause problems within a supply chain and the project driver for this work was clearly inventory reduction. However, while excessive inventory is clearly a problem and organizations should strive to reduce unnecessary inventory as much as possible, there is an optimal amount of inventory that should be maintained and that amount is rarely zero. Inventory is held for a variety of reasons and can be utilized as a tool to countermeasure the primary factors that influence inventory requirements: customer demand, demand variability, production yield, production yield variability, lead time, lead time variability, and desired customer service levels. Alcoa utilizes inventory as a countermeasure within their supply chain for a variety of reasons. Customers are demanding increasing levels of service; and their demand patterns are variable. Replenishment lead times are long (on the order of months) and variable. Davenport Works is striving to achieve economies of scale; and their production yields are variable and often times deviate significantly from the customer's forecasted consumption rate. Currently, high levels of inventory are being maintained throughout the supply chain; and desired customer service level targets are not being met. AMP has no formal methodologies to both characterize the reasons why inventory is being maintained and to determine what inventory requirements they need to satisfy each specific customer program. In addition, AMP is driving cost reductions throughout the entire organization. This is forcing the organization to justify the inventory they currently have and also putting pressure on the organization to reduce inventories throughout the supply chain. This thesis has three primary objectives. Firstly, to provide a detailed analysis of the entire AMP supply chain for its European customers and articulate the reasons why AMP is maintaining inventory. This includes a discussion about supply chains, supply chain management, and the role of inventory in the supply chain. Secondly, to describe a methodology, which can be applied to engineer inventory levels for each product. The base stock model was used for this and is an excellent tool to demonstrate how supply chain variables impact inventory requirements, target areas for improvement, and quantify inventory requirements in a systematic manner. Thirdly, to provide recommendations to improve overall supply chain performance and optimize inventories.
by Brian A. Urkiel.
S.M.
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Thiele, Aurélie 1977. "A robust optimization approach to supply chains and revenue management." Thesis, Massachusetts Institute of Technology, 2004. http://hdl.handle.net/1721.1/16693.
Full textAbstract:
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2004.Includes bibliographical references (p. 171-176).
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
The contribution of this thesis is to provide a tractable framework for supply chains and revenue management problems subject to uncertainty that gives insight into the structure of the optimal policy and requires little knowledge of the underlying probability distributions. Instead, we build upon recent advances in the field of robust optimization to develop models of uncertainty that make few probabilistic assumptions and have an adjustable level of conservatism to ensure performance. Specifically, we consider two classes of robust optimization approaches. First, we model the random variables as uncertain parameters belonging to a polyhedral uncertainty set, and optimize the system against the worst-case value of the uncertainty in the set. The polyhedron is affected by budgets of uncertainty, which reflect a trade-off between robustness and optimality. We apply this framework to supply chain management, show that the robust problem is equivalent to a deterministic problem with modified parameters, and derive the main properties of the optimal policy. We also explore a second approach, which builds directly on the historical realizations of uncertainty, without requiring any estimation. In that model, a fraction of the best cases are removed to ensure robustness, and the system is optimized over the sample average of the remaining data. This leads to tractable mathematical programming problems. We apply this framework to revenue management problems, and show that in many cases, the optimal policy simply involves an appropriate ranking of the historical data. Robust optimization emerges as a promising methodology to address a wide range of management problems subject to uncertainty, in particular in a dynamic setting, as it leads to
(cont.) representations of randomness that make few assumptions on the underlying probabilities, remain numerically tractable, incorporate the decision-maker's risk aversion, and provides theoretical insights into the structure of the optimal policy.
by Aurélie Thiele.
Ph.D.
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Birenbaum, Jeffrey (Jeffrey P. ). "Inbound supply chain optimization with ship-mode variation in a fixed-capacity fulfillment center." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/117981.
Full textAbstract:
Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, 2018.Thesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, in conjunction with the Leaders for Global Operations Program at MIT, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 73-74).
each of the past two years. In order to scale with expected continued sales growth, Amazon has been investing heavily in its inbound supply chain, where product is received and allocated to various nodes, with cross-dock facilities, Amazon Robotics fulfillment centers and traditional fulfillment centers constituting a multi-echelon distribution network. In an Amazon Robotics fulfillment center, robotic drives retrieve and deliver portable inventory pods, where product is stowed and picked at fixed stations. Currently, approximately 65% of associate hours within the inbound department are utilized in the direct process of stow, while the other 35% of associate hours in the inbound department are utilized in support of the stow process in tasks such as corrugate removal and product container management. As a result, there is a continued emphasis on improving the efficiency of the nonvalue added tasks utilized in support of the stow process in order to utilize as many hours as possible in the value-added stow process. This thesis proposes a linear optimization-based analysis framework and capital allocation model that can be utilized to determine the investment viability for different automation systems and process improvements, which could improve efficiency and reduce overall cost in the Amazon Robotics fulfillment centers. This is especially the case within those fulfillment centers that are labor constrained. Labor constraints within a fulfillment center result in artificial limits set within Amazon's inventory placement algorithm, changing the origin of the shipment of product(s) to customers, which results in additional outbound transportation cost. This study will uncover unrealized cost-improvement areas by suggesting an inbound conveyance solution that can improve upon the current human-powered inbound system, and provides further areas of investigation for additional improvement. Implementation of the selected automation solution reduces inbound department hours by -3% with a payback period of -0.93 years for the fulfillment center in question, while improving labor-constrained fulfillment center capacity by as much as 1 %, and suggests further areas of investigation that can improve overall cost within the inbound supply chain by over 10%.
by Jeffrey Birenbaum.
M.B.A.
S.M.
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Huang, Jing. "Resource Management and Sourcing Strategies in Supply Chain Coordination under an Uncertain Environment." Ohio University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1354756891.
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Choi, Jaein. "Algorithmic Framework for Improving Heuristics in Stochastic, Stage-Wise Optimization Problems." Diss., Georgia Institute of Technology, 2004. http://hdl.handle.net/1853/4954.
Full textAbstract:
Algorithmic Framework for Improving Heuristics in
Stochastic, Stage-Wise Optimization Problems
Jaein Choi
172 Pages
Directed by Dr. Jay H. Lee and Dr. Matthew J. Realff
The goal of this thesis is the development of a computationally tractable solution method for stochastic, stage-wise optimization problems. In order to achieve the goal, we have developed a novel algorithmic framework based on Dynamic Programming (DP) for improving heuristics. The propose method represents a systematic way to take a family of solutions and patch them together as an improved solution. However, patching is accomplished in state space, rather than in solution space. Since the proposed approach utilizes simulation with heuristics to circumvent the curse of dimensionality of the DP, it is named as Dynamic Programming in Heuristically Restricted State Space. The proposed algorithmic framework is applied to stochastic Resource Constrained Project Scheduling problems, a real-world optimization problem with a high dimensional state space and significant uncertainty equivalent to billions of scenarios. The real-time decision making policy obtained by the proposed approach outperforms the best heuristic applied in simulation stage to form the policy. The proposed approach is extended with the idea of Q-Learning technique, which enables us to build empirical state transition rules through simulation, for stochastic optimization problems with complicated state transition rules. Furthermore, the proposed framework is applied to a stochastic supply chain management problem, which has high dimensional action space as well as high dimensional state space, with a novel concept of implicit sub-action space that efficiently restricts action space for each state in the restricted state space. The resulting real-time policy responds to the time varying demand for products by stitching together decisions made by the heuristics and improves overall performance of the supply chain. The proposed approach can be applied to any problem formulated as a stochastic DP, provided that there are reasonable heuristics available for simulation.
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Fetcho-Phillips, Kacey L. (Kacey Lynn). "Capacity analysis, cycle time optimization, and supply chain strategy in multi-product biopharmaceutical manufacturing operations." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/66071.
Full textAbstract:
Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering; in conjunction with the Leaders for Global Operations Program at MIT, 2011.Cataloged from PDF version of thesis.
Includes bibliographical references (p. 99-104).
Application of system optimization theory, supply chain principles, and capacity modeling are increasingly valuable tools for use in pharmaceutical manufacturing facilities. The dynamics of the pharmaceutical industry - market exclusivity, high margins, product integrity and contamination constraints - coupled with increasing cost pressures, demand for specialized products increase, and growing industry complexity makes analytical business decisions necessary to sustain competitive advantage. The united application of capacity modeling, system optimization, and supply chain analysis tools, paired with implementation strategies on a multi-product vaccine production system are detailed to address important business difficulties.
by Kacey L. Fetcho-Phillips.
S.M.
M.B.A.
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DiAndreth, Christopher. "Optimization of downstream supply chain product flow based on an integrated cost-to-deliver perspective." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/122589.
Full textAbstract:
Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, 2019, In conjunction with the Leaders for Global Operations Program at MITThesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2019, In conjunction with the Leaders for Global Operations Program at MIT
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 63-65).
As Boston Scientific's supply chain becomes more versatile in mixing their supply networks across divisions, there is new opportunity to re-optimize product flow downstream of manufacturing based on unique product attributes and network capabilities instead of solely legacy divisional flow. The current organizational structure, methods, and systems prompts product flow to be optimized within functional silos. However, there are no current methods or tools that readily enable management to evaluate the total system in an integrative manner or with respect to specific product attributes. This project aims to improve BSC's ability to determine optimal product flow by introducing a tool that optimizes across the downstream supply chain via an integrative perspective that accounts for product and network attributes.
The integration involves the major cost activities, such as freight, handling, and inventory costs, or what can be termed the total "Cost-to-Deliver" product from a manufacturing facility to end customers. The proposed optimization framework includes the inter-dependencies of cost drivers across the supply chain that are typically missed when solving in functional silos. We develop a decision support tool to determine optimal product flow across the various nodes within the downstream supply chain (manufacturing, sterilization, and multiple tiers of distribution centers) over a single period horizon that can be extend to multi-periods through a present value approach. This tool enables the decision maker to compare directly the trade-offs between two different constrained flows, as well as vary product parameters within this scenario comparison to uncover ideal product segmentation with respect to flow decisions.
To demonstrate the value for the tool, we used it to segment products with respect to the choice of transportation mode on a freight lane. We find that changing the standard transportation mode for several current products would yield five-year net present value savings of 10-35% of their current annual cost-to-deliver. Ultimately the insights gained, and framework leveraged, are relevant to other industries with multinodal supply chains with high-mix products and not just constrained to the Medical Device industry.
by Christopher DiAndreth.
M.B.A.
S.M.
M.B.A. Massachusetts Institute of Technology, Sloan School of Management
S.M. Massachusetts Institute of Technology, Department of Mechanical Engineering
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Masse, Brian Robert. "Inventory optimization in high volume aerospace supply chains." Thesis, Massachusetts Institute of Technology, 2011. http://hdl.handle.net/1721.1/66057.
Full textAbstract:
Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; in conjunction with the Leaders for Global Operations Program at MIT, 2011.Cataloged from PDF version of thesis.
Includes bibliographical references (p. [51]).
The supply chains of aerospace products can be complex, involving thousands of components per product and hundreds of vendors spaced out over an increasingly global landscape. Managing all inputs necessary for these complex aerospace supply chains is a task that is critical to the success of any firm and requires extensive planning, close partnerships, and detailed analysis. This thesis outlines a system for optimal safety stock management in high volume aerospace supply chains. Given such supply chain parameters as component inventory values, procurement and manufacturing lead times, demand distributions, and bills of material, the ideal safety stock locations and sizes which result in minimal overall inventory levels are calculated by a nonlinear optimization program. With this safety stock structure, aerospace firms can operate their supply chains with higher customer service rates and lower inventory levels. A methodology is also developed to help aerospace companies improve their existing supply chains as efficiently as possible. Considering the limited time and resources available, a company may not be able to enhance all areas of its operations and determining where to improve with the greatest effect on customer service levels and inventory can be difficult. The framework developed provides general guidelines to ensure improvement resources are being deployed most efficiently. Finally, business environment and operations considerations are discussed to aid companies in the process of implementing supply chain improvements and instituting organizational change.
by Brian Robert Masse.
S.M.
M.B.A.
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Dhumal, Parag. "Supply Chains with Bi-level Demand: Analyzing the Impact of Inventory Policies." University of Toledo / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1197406635.
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