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Dissertations / Theses on the topic 'Stochastic inventory model'
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Lee, Yun Shin. "Essays on stochastic forecasting and inventory planning under model uncertainty." Thesis, University of Cambridge, 2011. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.609889.
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Ozener, Okan Orsan. "A Capacitated Inventory Model With A Fixed Ordering Cost Under Stochastic Demand." Master's thesis, METU, 2003. http://etd.lib.metu.edu.tr/upload/4/1094234/index.pdf.
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lyer, Nurani Vishwanathan Parameshwaran. "Optimal inventory model for managing demand-supply mismatches for perishables with stochastic supply." Thesis, Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/122255.
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Thesis: M. Eng. in Supply Chain Management, Massachusetts Institute of Technology, Supply Chain Management Program, 2019Cataloged from PDF version of thesis.
Includes bibliographical references (pages 52-53).
While festivals bring a reason to cheer for everyone, businesses dealing with a spike in demand for perishables may have to live with the misery of lost sales and/or expired items. In the case of the dairy industry that deals with liquid milk, both raw material, and finished goods are perishable, which implies that merely stockpiling inventory of either item, without paying attention to potential inventory losses, cannot be an optimal strategy. In developing countries, the supplier base for perishables like milk, fruits, vegetables, flowers, etc. mostly comprise of small farmers instead of corporate/professional agencies, thus leading to supply variability. During special occasions like festivals, as individuals set aside more of the raw material for their own consumption, we encounter a reduction in supply. Around the same time, we notice a spike in customer demand, leading to a demand-supply mismatch. Companies dealing with perishables need an analytical approach to manage this.
In this thesis, we present a framework to address this problem of intermittent demand-supply mismatch using a 3-stage stochastic optimization model. We decide on the sourcing targets, the production plans based on supply realized, and finally, the dispatch plan based on orders received. As a case study, we analyze the operations and data from a private dairy company in eastern India, to understand the research problem and the applicability of the resulting model. We notice the impact of demand spikes and supply reduction in two areas: we increase supply targets in the periods preceding the demand spike; and we increase supply targets in periods when supply is expected to decrease, while demand is as usual. When there are multiple festival days within the time series, the compounding of impact depends on the sequencing of the events.
Finally, when we introduce the realistic constraint that the supply target needs to be constant throughout the time series, we see a degradation in the profitability, as we need to tradeoff between lost sales and wasted products. While the focus of this case study is the dairy industry, the conclusions from this research are broadly applicable to other industries dealing with perishables.
by Vishwanathan Parameshwaran lyer Nurani.
M. Eng. in Supply Chain Management
M.Eng.inSupplyChainManagement Massachusetts Institute of Technology, Supply Chain Management Program
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Gimpl-Heersink, Lisa, Christian Rudloff, Moritz Fleischmann, and Alfred Taudes. "Integrating Pricing and Inventory Control: Is it Worth the Effort?" SpringerOpen, 2008. http://dx.doi.org/10.1007/BF03342705.
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In this paper we first show that the gains achievable by integrating pricing and inventory control are usually small for classical demand functions. We then introduce reference price models and demonstrate that for this class of demand functions the benefits of integration with inventory control are substantially increased due to the price dynamics. We also provide some analytical results for this more complex model. We thus conclude that integrated pricing/inventory models could repeat the success of revenue management in practice if reference price effects are included in the demand model and the properties of this new model are better understood. (authors' abstract)
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Guzman, Pamela, Franklin Montalvo, Edgardo Carvallo, and Carlos Raymundo. "Implementation of a process management model and inventory control to increase the level of service in the after-sales area of industrial equipment." Latin American and Caribbean Consortium of Engineering Institutions, 2019. http://hdl.handle.net/10757/656260.
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Currently, many industrial companies generate many losses in their after sales this is generated to an error in the control of inventories and in turn in a mishandling of their assets through their processes, therefore the present research proposes a management model of processes and control of inventories in order to reduce customer losses due to the large number of existing complaints and thus increase sales. Therefore, the process management model, which will contribute to the standardization, optimization and control of its critical processes, and for which indicators, procedures and policies will be proposed for each stage of the process in order to measure its efficiency and effectiveness for correct decision making. With respect to the control of inventories, it is proposed to make a segmentation of the products, which allows the identification of the most important products for the company, to then design a demand forecast model for families of products that will later be individualized considering their factors initial and finally using an inventory management model will obtain the optimal quantity of spare parts order to use in the technical service of the equipment reducing the annual costs related to the inventory.
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Ozpamukcu, Serkan. "An Assessment Of A Two-echelon Inventory System Againstalternative Systems." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613949/index.pdf.
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In this study, we focus on a real life problem that involves a single item which is
used in military operations. The items in use fail according to a Poisson process
and lead times are deterministic. Four alternative inventory control models are
developed. Among these models, a two-echelon system consisting of a depot in
the upper and several bases in the lower echelon is operated currently. This
system is compared to a single-echelon system that consists of several bases. The
comparison reveals the importance of the holding cost incurred for the items intransit
between the depot and the base which is ignored in most of the studies in
literature. Both the two and single-echelon models are also extended to have
repair ability. A continuous-review base-stock policy is used for all models.
Exact models are formulated. The results are obtained under various lead time,
unit costs and demand parameters. Results of four different settings are compared
and the findings are reported.
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Liang, Hongyan. "Three Essays on Performance Evaluation in Operations and Supply Chain Management." Kent State University / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=kent1504827189112207.
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Červenka, Daniel. "Aplikace metod optimalizace zásob v dodavatelských řetězcích." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-150222.
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As in the stock of trading business is allocated a large part of the capital resources, it is necessary to determine the manner of their control. For this purpose a number of models were developed. Before application to the specific case, these models must be properly adjusted to ensure conformity with reality. The aim of this thesis is to optimize the inventory management of electronic commerce. The stochastic model with loss from unfulfilled orders was chosen as default. First, the necessary adjustments were made to the model and defined input parameters. After filling model with real data, the optimum values of the monitored variables were obtained. The last part deals with the influence of changes in input parameters on the optimal value of variables. Use of the model is not limited to this particular case. Without major modifications, the model is also applicable to other similar problems.
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Tai, Hoi-lun Allen. "Stochastic models for inventory systems and networks." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B37681758.
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Schwarz, Maike [Verfasser]. "Stochastic Models in Inventory Theory / Maike Schwarz." Aachen : Shaker, 2004. http://d-nb.info/1172610304/34.
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Tai, Hoi-lun Allen, and 戴凱倫. "Stochastic models for inventory systems and networks." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B37681758.
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Kröckel, Silke. "Stochastic production-inventory systems with significant setup times." Diss., Georgia Institute of Technology, 2002. http://hdl.handle.net/1853/24367.
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Ortiz, Olga L. "Stochastic inventory control with partial demand observability." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/22551.
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Thesis (Ph. D.)--Industrial and Systems Engineering, Georgia Institute of Technology, 2008.Committee Co-Chair: Alan L Erera; Committee Co-Chair: Chelsea C, White III; Committee Member: Julie Swann; Committee Member: Paul Griffin; Committee Member: Soumen Ghosh.
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Avital, Ittai. "Two-period, stochastic, supply-chain models with recourse for Naval surface warfare /." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2004. http://library.nps.navy.mil/uhtbin/hyperion/04Mar%5FAvital.pdf.
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Thesis (M.S. in Operations Research)--Naval Postgraduate School, March 2004.Thesis advisor(s): R. Kevin Wood, Moshe Kress, Gerald G. Brown. Includes bibliographical references (p. 47-48). Also available online.
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Moryadee, Chanicha. "Optimisation models and heuristic methods for deterministic and stochastic inventory routing problems." Thesis, University of Portsmouth, 2017. https://researchportal.port.ac.uk/portal/en/theses/optimisation-models-and-heuristic-methods-for-deterministic-and-stochastic-inventory-routing-problems(182ea07e-ef7b-4b4c-85c9-7570e8e5a160).html.
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The inventory routing problem (IRP) integrates two components of supply chain management, namely, inventory management and vehicle routing. These two issues have been traditionally dealt with problems in the area of logistics separately. However, these issues may reduce the total costs in which the integration can lead a greater impact on overall system performance. The IRP is a well-known NP-hard problem in the optimisation research publication. A vehicle direct delivery from the supplier with and without transhipments (Inventory Routing Problem with Transhipment, IRPT) between customers in conjunction with multi-customer routes in order to increase the flexibility of the system. The vehicle is located at a single depot, it has a limited capacity for serving a number of customers. The thesis is focused on the two main aspects: (1) Development of the optimisation models for the deterministic and stochastic demand IRP and IRPT under ML/OU replenishment polices. On the deterministic demand, the supplier deliveries products to customers whose demands are known before the vehicle arrives at the customers’ locations. Nevertheless, the stochastic demand, the supplier serves customers whose actual demands are known only when the vehicle arrives at the customers’ location. (2) Development of integrated heuristic, biased probability and simulation to solve these problems. The proposed approaches are used for solving the optimisation models of these problem in order to minimise the total costs (transportation costs, transhipment costs, penalty costs and inventory holding costs). This thesis proposed five approaches: the CWS heuristic, the Randomised CWS heuristic, the Randomised CWS and IG with local search, the Sim-Randomised CWS, and the Sim-Randomised CWS and IG with local search. Specifically, the proposed approaches are tested for solving the deterministic demand IRP and IRPT, namely, the IRP-based CWS, the IRP-based Randomised CWS, the IRP-based Randomised CWS and IG with local search. For the transhipment case are called the IRPT-based CWS, the IRPT-based Randomised CWS, and the IRP-based Randomised CWS and IG with local search. On the stochastic demand, these proposed approaches are named the SIRP-based Sim-Randomised CWS, the SIRPT-based Sim-Randomised CWS, the SIRP-based Sim-Randomised CWS and IG with local search, and the SIRPT-based Sim-Randomised CWS and IG with local search. The aim of using the sim-heuristic is to deal with stochastic demand IRP and IRPT, the stochastic behaviour is the realistic scenarios in which demand is used to be addressed using simulation. Firstly, the Sim-Randomised CWS approach, an initial solution is generated by Randomised CWS heuristic, thereafter an MCS is combined to provide further improvement in the final solution of the SIRP and the SIRPT. Secondly, the integration of Randomised CWS with MCS and IG with local search is solved on these problems. Using an IG algorithm with local search improved the solution in which it generated by Randomised CWS. The developed heuristic algorithms are experimented in several benchmark instances. Local search has been proven to be an effective technique for obtaining good solutions. In the experiments, this thesis considers the average over the five instances for each combination and the algorithms are compared. Thus, the IG algorithm and local search outperformed the solution of Sim-Randomised CWS heuristics and the best solutions in the literature. This proposed algorithm also shows a shorter computer time than that in the literature. To the best of the author’ knowledge, this is the first study that CWS, Randomised CWS heuristic, Sim-Randomised CWS and IG with local search algorithms are used to solve the deterministic and stochastic demand IRP and IRPT under ML/OU replenishment policies, resulting of knowledge contribution in supply chain and logistics domain.
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Cheaitou, Ali. "Stochastic models for production-Inventory planning : application to short life-cycle products." Châtenay-Malabry, Ecole centrale de Paris, 2008. http://www.theses.fr/2008ECAP1066.
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Dans le domaine du « Supply Chain Management » la source principale d’incertitude est la demande future. L’impact de l’incertitude de lademande sur les performances de la « Supply Chain » est important: par exemple, le taux mondial de rupture de stock, dans l’industrie dedistribution était en 2007 de 8. 3%. De l’autre côté, le taux mondial de produits invendus, dans la grande distribution, était en 2003 de 1%. Ces deux types de coûts, qui sont dus essentiellement à l’incertitude de la demande, représentent des pertes significatives pour lesdifférents acteurs de la « Supply Chain ». Dans cette thèse, on s’intéresse au développement de modèles mathématiques de planification de production et de gestion de stock, quiprennent en compte ce phénomène d’incertitude sur la demande, essentiellement pour de produits à court cycle de vie. On proposeplusieurs modèles de planification de production, à petit horizon de planification, qui prennent en compte les différents aspects de notreproblématique, telles que la remise à jour des prévisions de la demande et les options de retour « Payback » des produits. On souligne,dans ces modèles, un aspect important qui prend de l’ampleur à cause de la mondialisation, et qui est lié à la différence entre les coûtsde production des différents fournisseurs. . On propose à la fin de la thèse, un modèle généralisé qui pourrait être appliqué à des produitsà long cycle de vie, et qui exploite quelques résultats obtenus pour les produits à court cycle de vie. Tous ces modèles sont résolusanalytiquement ou bien numériquement en utilisant la programmation dynamique stochastiqueIn the Supply Chain Management domain, the main source of randomness is the future demand. The influence of this demand variabilityon the performance of the Supply Chain is very important: for example, in 2007 the global inventory shortage rate in the retail industrywere around 8. 3%. On the other hand, in 2003 the global Unsaleable products cost around 1% in the grocery industry. These two types ofcosts, which are mainly caused by the uncertainty of the future demand, represent important lost for the whole Supply Chain actors. This Ph. D. Dissertation aims at developing mathematical production planning and inventory management models, which take intoconsideration the randomness of the future demand in order to reduce its economic negative impact, essentially for short life cycleproducts. We provide many planning models that consider the main issues of the planning problems, such as the production capacities,the information updating processes, the supply contracts and the advanced capacity reservation in a total costs minimization context. Weconsider in these models some aspects that are not considered in the literature, such as the “Payback” or the return options. Weemphasize also on an important issue that characterize the globalization of the industry, which may be resumed in the difference betweenthe procurement costs of the different suppliers. This issue is considered in the most chapters presenting models for short life cycleproducts and in the last chapter it is generalized to a long life cycle products setting. All the presented models are solved eitheranalytically or numerically using the dynamic stochastic programming
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Sabouri, Alireza Bagh Abbas. "Applications of stochastic optimization models in patient screening and blood inventory management." Thesis, University of British Columbia, 2014. http://hdl.handle.net/2429/50494.
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This thesis comprises three chapters with applications of the stochastic optimization models in healthcare as a central theme. The first chapter considers a patient screening problem. Patients on the kidney transplant waiting list are at higher risk for developing cardiovascular disease (CVD), which makes them ineligible for transplant. Therefore, transplant centers screen waiting patients to identify patients with severe CVD. We propose a model for finding screening strategies, with the objective of minimizing sum of the expected screening cost and the expected penalty cost associated with transplanting an organ to an ineligible patient. Our results suggest that current screening guidelines, which are only based on patients' risk for developing CVD, are significantly dominated by policies that also consider factors related to patients' waiting time.
In the second chapter, we extend our results from the first chapter to the case of inspecting a vital component which is needed at a random future time when an emergency occurs. If the component is not operational at that time, the system incurs a large penalty, which we want to avoid through inspections and replacements. We propose a model and solution algorithm for finding an inspection policy that minimizes the infinite horizon discounted expected penalty, replacement, and inspection costs. We also discuss other structural properties of the solution, as well as insights based on numerical results.
In the third chapter, we consider inventory decisions regarding issuing blood in a hospital. This research is motivated by recent findings in medicine that the age of transfused blood can affect health outcomes, with older blood contributing to more complications. Current practice at hospital blood banks is to issue blood in order from oldest to youngest inventory, so as to minimize shortage. However, the conflicting objective of reducing the age of blood transfused requires an issuing policy that also depends on the inventory of units of different ages. We propose a model that balances the trade-off between the average age of blood transfused and the shortage rate. Our numerical results suggest we can significantly reduce the age of transfused blood with a relatively small increase in the shortage rate.Business, Sauder School of
Graduate
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Avital, Ittai. "Chance-constrained missile-procurement and deployment models for Naval Surface Warfare /." Diss., Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2005. http://library.nps.navy.mil/uhtbin/hyperion/05Mar%5FAvital.pdf.
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Zahrn, Frederick Craig. "Studies of inventory control and capacity planning with multiple sources." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/29736.
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Thesis (Ph.D)--Industrial and Systems Engineering, Georgia Institute of Technology, 2010.Committee Co-Chair: John H. Vande Vate; Committee Co-Chair: Shi-Jie Deng; Committee Member: Anton J. Kleywegt; Committee Member: Hayriye Ayhan; Committee Member: Mark E. Ferguson. Part of the SMARTech Electronic Thesis and Dissertation Collection.
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Gregůrek, Jakub. "Řešení speciálních modelů zásob firmy Dencop Lighting." Master's thesis, Vysoká škola ekonomická v Praze, 2008. http://www.nusl.cz/ntk/nusl-4402.
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The thesis is focused on finding optimal solution of stock company Dencop Lighting spol. s.r.o. At the very beginning of the thesis there is a brief characteristic of Dencop Lighting, their market aims and goals. After this view we are going to introduce you warehouse systems. There are analysis of products, their selection, flows and potentials for company. After completing product analysis we are going to focus on key factors of optimalization. There are mentioned many ways of optimalization with their advantages and disadvantages. Deterministic and stochastic methods are included as well. For better illusion in real live you can find added CD at the bottom of the thesis. Using guide of this software with detailed information about functions is in last pages of the thesis.
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Megahed, Aly. "Supply chain planning models with general backorder penalties, supply and demand uncertainty, and quantity discounts." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/54011.
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In this thesis, we study three supply chain planning problems. The first two problems fall in the tactical planning level, while the third one falls in the strategic/tactical level. We present a direct application for the first two planning problems in the wind turbines industry. For the third problem, we show how it can be applied to supply chains in the food industry.
Many countries and localities have the explicitly stated goal of increasing the fraction of their electrical power that is generated by wind turbines. This has led to a rapid growth in the manufacturing and installation of wind turbines. The globally installed capacity for the manufacturing of different components of the wind turbine is nearly fully utilized. Because of the large penalties for missing delivery deadlines for wind turbines, the effective planning of its supply chain has a significant impact on the profitability of the turbine manufacturers. Motivated by the planning challenges faced by one of the world’s largest manufacturers of wind turbines, we present a comprehensive tactical supply chain planning model for manufacturing of wind turbines in the first part of this thesis. The model is multi-period, multi-echelon, and multi-commodity. Furthermore, the model explicitly incorporates backorder penalties with a general cost structure, i.e., the cost structure does not have to be linear in function of the backorder delay. To the best of our knowledge, modeling-based supply chain planning has not been applied to wind turbines, nor has a model with all the above mentioned features been described in the literature. Based on real-world data, we present numerical results that show the significant impact of the capability to model backorder penalties with general cost structures on the overall cost of supply chains for wind turbines.
With today’s rapidly changing global market place, it is essential to model uncertainty in supply chain planning. In the second part of this thesis, we develop a two-stage stochastic programming model for the comprehensive tactical planning of supply chains under supply uncertainty. In the first stage, procurement decisions are made while in the second stage, production, inventory, and delivery decisions are made. The considered supply uncertainty combines supplier random yields and stochastic lead times, and is thus the most general form of such uncertainty to date. We apply our model to the same wind turbines supply chain. We illustrate theoretical and numerical results that show the impact of supplier uncertainty/unreliability on the optimal procurement decisions. We also quantify the value of modeling uncertainty versus deterministic planning.
Supplier selection with quantity discounts has been an active research problem in the operations research community. In this the last part of this thesis, we focus on a new quantity discounts scheme offered by suppliers in some industries. Suppliers are selected for a strategic planning period (e.g., 5 years). Fixed costs associated with suppliers’ selection are paid. Orders are placed monthly from any of the chosen suppliers, but the quantity discounts are based on the aggregated annual order quantities. We incorporate all this in a multi-period multi-product multi-echelon supply chain planning problem and develop a mixed integer programming (MIP) model for it. Leading commercial MIP solvers take 40 minutes on average to get any feasible solution for realistic instances of our model. With the aim of getting high-quality feasible solutions quickly, we develop an algorithm that constructs a good initial solution and three other iterative algorithms that improve this initial solution and are capable of getting very fast high quality primal solutions. Two of the latter three algorithms are based on MIP-based local search and the third algorithm incorporates a variable neighborhood Descent (VND) combining the first two. We present numerical results for a set of instances based on a real-world supply chain in the food industry and show the efficiency of our customized algorithms. The leading commercial solver CPLEX finds only a very few feasible solutions that have lower total costs than our initial solution within a three hours run time limit. All our iterative algorithms well outperform CPLEX. The VND algorithm has the best average performance. Its average relative gap to the best known feasible solution is within 1% in less than 40 minutes of computing time.
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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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"Essays on stochastic inventory model." Thesis, 2011. http://library.cuhk.edu.hk/record=b6075128.
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The first essay considers a dynamic non-stationary inventory problem in which replenishment is made in fixed lot sizes (e.g., in full truckloads or full containers). We consider two separate cases: one with exogenous pricing and the other with endogenous pricing. In the first case (exogenous pricing), we show that when the ordering cost contains only a variable component, the reorder-point lot-size policy or (r, Q) policy is optimal for both single-stage and multi-echelon inventory systems. In the presence of a fixed cost, we establish the optimality of batch based (s, S ) policies for the single-stage inventory system. In the second case (endogenous pricing), we show that when the demand function has the additive form and there is only a variable ordering cost, the (r,Q) list-price policy is optimal for the single-stage system, where inventory replenishment follows an (r,Q) policy and the optimal price in each period depends on the order-up-to level.The second essay analyzes a periodic-review, stochastic, inventory-control system in which the fixed order-cost is a step function of the order size. In particular, if the order size is within a specified limit, C, then the setup cost is K1; otherwise it is K2, where K2 ≥ K1. This cost structure is motivated from some industrial applications and transportation/production contracts used in practice. Under the condition that K1 ≤ K 2 ≤ K1, we introduce a new concept called C - (K1 ≤ K 2) convexity, which enables us to partially characterize the structure of an optimal ordering policy. For the general condition K 1 ≤ K2 , the analysis is facilitated with a different notion called strong K-convexity. Based on this analysis, we provide a partial characterization of the optimal policy and construct an easy-to-implement heuristic method that has near-optimal performance in random test instances. Our study extends or redevelops (with different techniques) several existing results in the literature.
The third essay studies a firm's periodic-review production/inventory ordering decisions when the next period's setup cost depends on the quantity produced/ ordered in the current period. In particular, if the current period's production/order quantity exceeds a specified threshold value, the system starts the next period in a "warm" state and no fixed setup cost is incurred; otherwise the state is considered "cold" and a positive setup cost is required for production/ ordering. We develop a dynamic programming formulation of the problem and provide a partial characterization of the optimal policy under the assumption that the demands follow a Polya or Uniform distribution. We use the structural results to develop fairly simple heuristic policies, which perform highly effectively in our computational experiments.
With increased globalization and competition in the current market, supply chain has become longer and more complicated than ever before. An effective and efficient supply chain is crucial and essential to a successful firm. In a supply chain, inventories are a very important component as the investment in inventories is enormous. This dissertation consists of three essays related to stochastic inventory management.
Yang, Yi.
Adviser: Youhua Chen.
Source: Dissertation Abstracts International, Volume: 73-04, Section: B, page: .
Thesis (Ph.D.)--Chinese University of Hong Kong, 2011.
Includes bibliographical references (leaves 145-151).
Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. Ann Arbor, MI : ProQuest dissertations and theses, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Abstract also in Chinese.
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Liu, Jun. "A Stochastic Inventory Model with Price Quotation." Thesis, 2009. http://hdl.handle.net/1807/17794.
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This thesis studies a single item periodic review inventory problem with stochastic demand, random price and quotation cost. It differs from the traditional inventory model in that at the beginning of each period, a decision is made whether to pay the quotation cost to get the price information. If it is decided to request a price quote then the next decision is on how many units to order; otherwise, there will be no order.
An (r, S1, S2) policy with r < S2, S1 <= S2 is proposed for the problem with two prices. It prescribes that when the inventory is less than or equal to r, the price quotation is requested; if the higher price is quoted, then order up to S1, otherwise to S2. There are two cases, r < S1 or S1 <= r. In the first case, every time the price is quoted, an order is placed. It is a single reorder point two order-up-to levels policy that can be considered as an extension of the (s, S) policy. In the second case, S1 <= r, it is possible to “request a quote but not buy” if the quoted price is not favorable when the inventory is between S1 and r.
Two total cost functions are derived for the cases r < S1 <= S2 and S1 <= r < S2 respectively. Then optimization algorithms are devised based on the properties of the cost functions and tested in numerical study. The algorithms successfully find the optimal policies in all of the 135 test cases. Compared to the exhaustive search, the running time of the optimization algorithm is reduced significantly. The numerical study shows that the optimal (r, S1, S2) policy can save up to 50% by ordering up to different levels for different prices, compared to the optimal (s, S) policy. It also reveals that in some cases it is optimal to search price speculatively, that is with S1 < r, to request a quote but only place an order when the lower price is realized, when the inventory level is between S1 and r.
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KoYu, Fu, and 傅科瑜. "Stochastic inventory model with quantity and freight discounts integration." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/28793446160021067942.
Full textAbstract:
碩士國立臺中技術學院
事業經營研究所
96
In supply chain management, transportation and inventory problems are very important. In the traditional inventory models, transportation cost is implicitly assumed being controlled by the supplier, so it is treated as a part of unit cost or included in the ordering cost, which is independent of delivery lot size. Thus, the effect of transportation cost could not reflect on management strategy completely. This study considers the continuous review inventory system with backorders, where various mixed types of freight discounts (all-weight/incremental weight) and quantity discounts (all-units/increment) are incorporated. Also, two special distributions, normal and uniform, are adopted to formulate the stochastic demand during lead time. For each discount policies, we develop solution procedures to find the optimal order quantity and reorder point such that the expected total annual cost is minimized. Furthermore, the results of proposed models are illustrated by numerical experiments, and sensitivity analysis is performed to examine the effect of problem parameters on the optimal policies. Comparing with the results of independent decision model where transportation cost is considered separately, the cost savings can be obtained using the proposed models in this study, and the case of dual all-units discounts has the great effect on cost savings.
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Hung, Yu-Han, and 洪郁涵. "An integrated inventory model with emission reduction investment under stochastic demand." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/vg2jn2.
Full textAbstract:
碩士國立臺中科技大學
流通管理系碩士班
107
Global warming and greenhouse gas emission have become an environmental issue now, so many studies related to the production and inventory problems begin to discuss carbon emission policies, or further consider through investing green technology to reduce carbon emission. The idea is by making better decisions or operating methods to achieve the objective of social environmental sustainability. This study establishes a vender-buyer integrated inventory model under stochastic demand with regard to two carbon emission policies (tax and cap-and-trade) and emission reduction investment plan. The objective is to find the optimal investing and inventory strategy for the model, which decision variables are order quantity, reorder point, number of shipments, and amount of emission reduction investment, so as to minimize the expected total cost. Besides, for the lead-time demand, we consider the normal distribution case and distribution free case. We use numerical example to illustrate the results of proposed models and perform sensitivity analysis. The numerical results show that comparing the tax policy model with emission reduction investment to the traditional model, the total carbon emission is reduced. Comparing the cap-and-trade policy model with emission reduction investment to the traditional model, both the expected total cost and total carbon emission are reduced.
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"An inventory model with stochastic leadtime, partial shipment, and delivery information delay." 2005. http://library.cuhk.edu.hk/record=b5892703.
Full textAbstract:
Xie Lei.Thesis (M.Phil.)--Chinese University of Hong Kong, 2005.
Includes bibliographical references (leaves 50-53).
Abstracts in English and Chinese.
Chapter 1 --- Introduction --- p.1
Chapter 1.1 --- Related Literature --- p.2
Chapter 2 --- Notations and Model Formulation --- p.8
Chapter 3 --- The Optimal Replenishment Policy --- p.15
Chapter 3.1 --- Preliminaries --- p.15
Chapter 3.2 --- The optimal replenishment policy at the second decision point --- p.17
Chapter 3.3 --- The optimal replenishment policy at the first decision point --- p.19
Chapter 4 --- Specialized Case: No Delivery Information Delay Model --- p.21
Chapter 4.1 --- Special Case 1: The Realized Proportional Factor rt = 0 --- p.23
Chapter 4.2 --- Special Case 2: The Realized Proportional Factor rt = 1 --- p.23
Chapter 4.3 --- Comparison of the Two Special Cases --- p.24
Chapter 4.4 --- "The Case with Partial Delivery (rt e (0,1))" --- p.26
Chapter 4.5 --- Comparison of the Delivery Information Delay Model and the No Delivery Information Delay Model --- p.33
Chapter 5 --- Nonoptimality of a Base-Stock Policy in Numerical Examples --- p.36
Chapter 6 --- Conclusion and Future Work --- p.39
Chapter 6.1 --- Conclusion --- p.39
Chapter 6.2 --- Future Work --- p.40
Chapter 7 --- Appendix --- p.42
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Fichtinger, Johannes. "The single-period inventory model with spectral risk measures." Thesis, 2010. http://epub.wu.ac.at/1855/1/document.pdf.
Full textAbstract:
Inventory management and pricing decisions based on quantitative models both in industrial practice and academic works often rely on minimizing expected cost or maximizing expected revenues or profits, which refers to the concept of risk-neutrality of the decision maker. Although many useful insights in operational problems can be obtained by such an approach, it is well understood that incorporating attitudes toward risk is an important lever for building new theories in other fields such as economics and finance. The level of risk associated with an investment might be as important as the expected gain from the investment. Hence, it is necessary to find appropriate measures of risk and the appropriate objectives related to or including these risk measures for inventory control & pricing problems. After the axiomatic foundation of coherent risk measures the application of risk measures to inventory models such as Conditional Value-at-Risk (CVaR) or convex combinations of mean and CVaR became popular. In our work we apply spectral risk measures to the single-period, single-item, linear cost inventory control & pricing problem (also known as newsvendor problem) and derive optimal policies. By doing so, we are able to unify results obtained so far in the literature under the common concept of spectral risk measures for the case of zero and non-zero shortage penalty cost. In particular, we show convexity results and structural properties for the inventory control and, under some assumptions, unimodality results as well as structural properties for the joint inventory & pricing problem. An extensive numerical analysis illustrates the findings. (author's abstract)
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Hsieh, Pei-Fang, and 謝佩芳. "An Integrated Inventory and Transportation Planning Decision Model for a Perishable Product: Stochastic Demands." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/19235907797192999510.
Full textAbstract:
碩士國立中興大學
行銷學系
93
More and more competitors emerge in the business environment nowadays, many advantageous mechanisms such as optimization models and computerized analysis tools are designed to improve the operational performance and keep firms remain competitive under threats of increasing competition. Many studies reveal that various integrations claim many benefits. Some commodities are unstable and deteriorate as time goes by. In this study, a model that coordinates inventory and distribution decisions for a perishable product is discussed. We focus on a decision making which simultaneously take into account inventory levels and transportation planning for a perishable product with stochastic demands. The objective is to minimize the overall cost. Demands are assumed to be characterized by a random variable that follows a uniform probability distribution. An order-up-to-R policy is used and the decay proportion of inventory amount at each distribution center is assumed to be a constant. A genetic algorithm is adopted to determine the optimal values of target inventory levels for each distribution center. We test a number coordination of GA parameters to find the most appropriate combination. The sensitivity analyses for some important parameters are conducted by holding all other parameters unchanged.
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Chen, Shiau-yi, and 陳孝怡. "An integrated inventory and transportation planning model for perishable products under stochastic demands and fuzzy costs." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/13952464581966111999.
Full textAbstract:
碩士國立中興大學
行銷學系
93
The integrated planning is a critical issue among firms along a supply chain. For instance, Yokoyama (2001) considered the decision problem of determining the optimal target inventory levels and optimal transportation quantities from warehouses to retailing sites for each period in a finite planning horizon simultaneously by minimizing the expected total cost regarding inventory and transportation operations. However, certain types of products may deteriorate during storage. This paper intends to extend Yokoyama’s model by incorporating the perishable nature of goods. Besides, we also take into account the imprecise nature of related inventory costs by employing fuzzy numbers. A simulated annealing algorithm is designed to solve the proposed model and some numerical analyses and comparisons are also provided.
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俞玉琴. "The Inventory Model of Stochastic Demand that The Lead Time and The Order Quantity are Decision Variables." Thesis, 1996. http://ndltd.ncl.edu.tw/handle/00654515974270169075.
Full textAbstract:
碩士國防管理學院
資源管理研究所
84
The research of management of inventory is developed quite complet, as we know that the lead time is an important part in it. By control lead time, we can reduce the safety stock, teduce the capital burden, raise the service level for cutomers, adapt the circumstance of market and increase the capability of competition for enterprise. This paper is to present such a inventory model of stochastic demand that the lead time and order quantity are decision variables. The demand during the lead time follows different distribution, the total amount of stockouts can be divided two conditions of backorders and lost-sales, we try to find the finest policy for the lead time and order quantity. There are four chapters in this paper. Chapter one is preface, it wants to discuss motivation, objective, contents of research and reference revien of this paper. The main subject of chapter two is the demands during lead time which follows the Normal distribution and under the two conditions of backorders and lost-sales to find the optimal lead time and order quantity, then we employ the sensitivity analysis to gain the influence to optimal solution when parameters were changed and an example was used to explain. The demand during the lead time follows the Poisson distribution is discussed in chapter three, because the demands is a discrete parameter to we use the characteristics of optimal solution and the trial-and-error to get the optimal lead time and order quantity. This chapter is also to discuss the influence of optimal solution of the degree of sensitivity when the paramenters getting change, then we also provide an example to verify the model. Chapter four are conclusion and the research in the future. The main subject is to conclued the above modles, and given a suggest for the research in the future.
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Chao, Yu-Sian, and 趙育賢. "Three-echelon inventory model with stochastic demand and permissible delay in payments considering scenario of lead time differences and backorders." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/r5hqzk.
Full text
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Ciou, Jhih-Shin, and 邱志信. "A Study of Inventory Control Facing Demand Forecasted by Stochastic Bass Model Using the Third Generation Cell Phone Sales Data in Taiwan." Thesis, 2008. http://ndltd.ncl.edu.tw/handle/d6m436.
Full textAbstract:
碩士國立東華大學
全球運籌管理研究所
96
The product life cycles of modern merchandises, such as mobile phones, have been impacted by the evolution of innovative technology. The innovation of mobile phones turns the role of the cell phone from the traditional communication products into the multi-functional action goods. Under the situation of high popularity of mobile phones, the sales forecast of its product life cycles may lead a contribution to further realize the behavior of the market. A better realization of the market will have an opportunity to coordinate the supply of the demand to achieve a better inventory management. One of the most popular product life cycle models adopted in this research is Bass Model (1969). Bass model is dedicated not only to product life cycle but also to sales volume forecast. This paper first utilizes Bass model to forecast the mean demand along the product life cycle of the third generation (3G) cell phone sales data in Taiwan. Then, the variance of the cumulative sales volume is estimated by the method based on Stochastic Bass Model in Niu (2002). In order to catch the variance of the sales volume, this research proposes a try and error method to estimate the change of the demand. Based upon the estimated mean and variance of demand in each period, (s, S) inventory policy is utilized to illustrate the behavior of inventory supply of the demand. The results show that the forecasted demand matches real trend of the data, and the requirements of the supply seems to be bounded within a fixed range.
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Chen, Chih-Chung, and 陳志忠. "Stochastic Inventory Models with Holding Cost Reduction." Thesis, 2007. http://ndltd.ncl.edu.tw/handle/66564463833253602027.
Full textAbstract:
碩士國立臺中技術學院
事業經營研究所
95
In most of the early literature dealing with inventory problems, holding cost is viewed as a prescribed constant and is not subject to control. In practices, holding cost could be reduced by extra expenditure; in other words, it is controllable. Recently, Billington (2003) presented this idea and modified the classic EOQ model to include a reduction in the per-unit holding cost. One of the basic assumptions of EOQ model is that the demand is deterministic, while it is often with uncertainty. The aim of this research is to extend Billington’s work to the uncertain environments. In this thesis, we propose two stochastic inventory models with holding cost reduction, based on the well-known continuous review and periodic review inventory systems. The demand during lead time (continuous review) is formulated by the Normal and Laplace distributions, concerning the fast- and slow-moving items, so does the demand during protection interval (periodic review). The objective is to minimizing the expected total annual cost by simultaneously optimizing the order quantity/review period, reorder point/target level and per-unit holding cost. For each model, a solution procedure is developed to find the optimal solution. Numerical examples along with sensitivity analysis are provided to illustrate the results of proposed models.
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XU, ZHI-XIONG, and 徐智雄. "The Optimal Lead Time of Stochastic Inventory Models." Thesis, 1991. http://ndltd.ncl.edu.tw/handle/80526616060048355786.
Full text
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Zhang, Liqing. "Stochastic Dynamic Demand Inventory Models with Explicit Transportation Costs and Decisions." Thesis, 2011. http://hdl.handle.net/1969.1/150943.
Full textAbstract:
Recent supply chain literature and practice recognize that significant cost savings can be achieved by coordinating inventory and transportation decisions. Although the existing literature on analytical models for these decisions is very broad, there are still some challenging issues. In particular, the uncertainty of demand in a dynamic system and the structure of various practical transportation cost functions remain unexplored in detail. Taking these motivations into account, this dissertation focuses on the analytical investigation of the impact of transportation-related costs and practices on inventory decisions, as well as the integrated inventory and transportation decisions, under stochastic dynamic demand.
Considering complicated, yet realistic, transportation-related costs and practices, we develop and solve three classes of models: (1) Pure inbound inventory model impacted by transportation cost; (2) Pure outbound transportation models concerning shipment consolidation strategy; (3) Integrated inbound inventory and outbound transportation models. In broad terms, we investigate the modeling framework of vendor-customer systems for integrated inventory and transportation decisions, and we identify the optimal inbound and outbound policies for stochastic dynamic supply chain systems.
This dissertation contributes to the previous literature by exploring the impact of realistic transportation costs and practices on stochastic dynamic supply chain systems while identifying the structural properties of the corresponding optimal inventory and/or transportation policies. Placing an emphasis on the cases of stochastic demand and dynamic planning, this research has roots in applied probability, optimal control, and stochastic dynamic programming.
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Chuang, Bor-Ren, and 莊博仁. "A Study of Some Stochastic Inventory Models with Controllable Lead Time." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/73459749184109189802.
Full textAbstract:
博士淡江大學
管理科學學系
87
In inventory managerial strategies for a business enterprise, lead time plays an increasingly important role on the applications of business activities, and also has been a topic of interest for many researchers. In most of the early literature dealing with the inventory problems, either in deterministic or probabilistic model, lead time is always treated as a prescribed constant or a random variable. Recently, many researchers felt doubtful about the uncontrollability of lead time and further embarked on the analysis of controllable lead time associated with the continuous review ordering policy. However, their research conceptions are almost concentrated on solving the optimal order quantity and lead time but ignoring the fact that the effects of reorder point is also an important factor in inventory cost control. Therefore, for the continuous review ordering policy, we attempt to formulate some quantitative mathematical models to accommodate the different inventory features, and simultaneously optimize order quantity, lead time and reorder point. On the other hand, viewing the domain of the periodic review inventory policies, existing literature discussing the controllable lead time problems is quite few. For this reason, this thesis seeks to investigate the effects of lead time on the periodic review inventory model. And hence, another purpose in this thesis is to examine the periodic review inventory systems so as to look for their corresponding optimal ordering strategies. This thesis mainly focuses on the controllable lead time for the continuous and periodic review ordering policies. Under both of these two policies, we respectively propose five stochastic inventory mathematical models. In chapters 2 and 3, continuous review policy, order quantity, lead time and reorder point are viewed as decision variables. During the stockout period, four cases are considered: 1) Stockout cost term is included in the objective function for the normal demand model, 2) Stockout cost term is included in the objective function for the distribution free demand model (i.e., the probability distribution of lead time demand is unknown), 3) Instead of having a stockout cost term in the objective function, a service level constraint is taken into consideration for the normal demand model, and 4) Instead of having a stockout cost term in the objective function, a service level constraint is taken into consideration for the distribution free demand model. On the other hand, in order to fit the practical inventory demands, we further consider several general inventory problems in the real world but they seldom appear in the research literature, e.g. an arrival order lot containing defective items, quantity discounts and stochastic backorder rate. Additionally, for the periodic review inventory models in chapter 4, we present four models to analyze the controllable lead time. Namely, we consider two demand models that are normal and distribution free. Both of these models respectively involve two cases that stockout cost term is included in the objective function and stockout cost term in the objective function is replaced by a service level constraint, where review period and lead time are allowed as decision variables. Finally, based upon the framework of chapter 4, we further establish a (T,R,L) model in chapter 5 to agree with a more realistic behavior pattern of quantitative model. From numerical example provided, it indicates that this new (T,R,L) model can achieve a significant amount of savings and provide a higher service level than that in (T,L) model of chapter 4. Furthermore, for the formulated mathematical inventory models in chapter 2 and 4, we analyze the effects of parameters and give economic interpretation of the circumstances.
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"Optimal replenishment policy for a stochastic inventory system with random order setup cost." 2003. http://library.cuhk.edu.hk/record=b5891657.
Full textAbstract:
Zhang Han.Thesis (M.Phil.)--Chinese University of Hong Kong, 2003.
Includes bibliographical references (leaves 44-46).
Abstracts in English and Chinese.
Abstract --- p.i
Acknowledgement --- p.ii
Chapter 1 --- Introduction --- p.1
Chapter 2 --- Background Study --- p.4
Chapter 3 --- "The Cost Function under the (s,c2,c1, S) Policy" --- p.8
Chapter 4 --- "Determination of the Optimal (s,c2,c1,s) Policy" --- p.16
Chapter 4.1 --- "The Auxiliary Function lγ(s, c2, C1, 5)" --- p.16
Chapter 4.2 --- Optimizing Parameters of s(γ) and s(γ) --- p.18
Chapter 4.3 --- Optimizing Parameters c2 (γ) and c1 (γ) --- p.21
Chapter 5 --- "Algorithm for Computing the Optimal (s, c2, C1, S) Policy" --- p.27
Chapter 5.1 --- Brief Description of the Algorithm --- p.27
Chapter 5.2 --- The Statement of the Algorithm --- p.28
Chapter 5.3 --- Interpretation of the Algorithm --- p.29
Chapter 6 --- "The Optimality of the (s, c2，c1, S) Policy" --- p.31
Chapter 6.1 --- Average Cost Criterion --- p.31
Chapter 6.2 --- The Proof of Optimality --- p.34
Chapter 6.3 --- "Optimality Proof for the Modified (s,c2,C1,S) Policy in the Re- laxed Model" --- p.38
Chapter 6.3.1 --- Introduction of the Relaxed Model --- p.38
Chapter 6.3.2 --- Average Cost Criteria for the Relaxed Model --- p.38
Chapter 7 --- Conclusion --- p.42
Bibliography --- p.43
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Jo-LingLee and 李若菱. "Inventory replenishment models for items with a stochastic linear declining demand process." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/cwe2ps.
Full textAbstract:
碩士國立成功大學
工業與資訊管理學系
105
In this thesis, inventory replenishment models under stochastic declining demand process is investigated. When an item enters the terminating phase of its product life cycle, the mean demand rate decreases over time, where a non-homogeneous Poisson process with a linear declining mean is used to model this demand. The replenishment policies to meet the demand in the future are to be determined so as to optimize the total expected cost or the total expected profit. The expected cost model includes: setup or ordering cost, inventory carrying cost, lost sale cost of unsatisfied demand, and overstock cost at the end of planning horizon. The expected total cost and total profit models for the single stage procurement policy are developed. Using cost model as a basis, a multi-stage procurement model is also analyzed. Two efficient solution procedures are developed and tested to find the optimal replenishment policies. Extensive computational test has demonstrated the effectiveness of the approaches. When planning horizon is sufficiently long and multi-stage procurement policy is implemented, the average cost reduction is 38%, if compared with that of the single-stage procurement policy.
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LIN, YU-JEN, and 林裕仁. "A STUDY OF PERIODIC REVIEW INVENTORY MODELS WITH STOCHASTIC DEMAND DURING THE PROTECTION INTERVAL." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/62386072967098740865.
Full textAbstract:
博士淡江大學
管理科學研究所博士班
93
In most of the early literature dealing with the inventory problems, the research conceptions are mostly concentrated on the continuous review ordering policy. However, viewing the domain of the periodic review inventory policies, it is found that existing literature discussing the problem is not substantial. In order to provide the decision-maker with some perfect managerial strategies of inventory systems, in this thesis, we attempt to investigate the periodic review inventory systems so as to look for their corresponding optimal ordering strategies. In the inventory systems with controllable lead time, when unsatisfied demands occur, in order to reduce lost sales, we consider the supplier could offer a backorder price discount, so that more customers may prefer their demands to be backorders. Or the supplier may invest more capital to reduce lost sales rate through efforts such as staff training, procedural changes, or specialized equipment acquisition. This thesis mainly focuses on the ordering strategies of periodic review inventory models. Under the policies, we propose the inventory models with stochastic demands during the protection interval. In Chapter 2, when unsatisfied demand occurs, we formulate the stockout quantity including backorder price discounts models with controllable lead time. And then, in Chapter 3, we discuss the stockout quantity including backorder price discounts, when the reduction of lead time may accompany the reduction of ordering cost. In Chapters 4 and 5, we consider investing more capital to reduce lost sales rate. In Chapter 4, we formulate the models, including decision variables of periodic review, lost sales rate, and lead time. And in Chapter 5, we formulate the models including decision variables of periodic review, lost sales rate, and target level. For each chapter, we discuss two cases in our formulate inventory models. The first is the case where the demand during protection interval follows a normal distribution. In the second case, where the distributional form of protection interval demand is unknown but merely the mean and standard deviation are known, we apply the minimax distribution free approach to solve the optimal solution. Finally, concluding remarks are made in Chapter 6, and future research directions are proposed.
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Allgor, Russell, Stephen C. Graves, and Ping Josephine Xu. "Traditional Inventory Models in an E-Retailing Setting: A Two-Stage Serial System with Space Constraints." 2003. http://hdl.handle.net/1721.1/3922.
Full textAbstract:
In an e-retailing setting, the efficient utilization of inventory, storage space, and labor is paramount to achieving high levels of customer service and company profits. To optimize the storage space and labor, a retailer will split the warehouse into two storage regions with different densities. One region is for picking customer orders and the other to hold reserve stock. As a consequence, the inventory system for the warehouse is a multi-item two-stage, serial system. We investigate the problem when demand is stochastic and the objective is to minimize the total expected average cost under some space constraints. We generate an approximate formulation and solution procedure for a periodic review, nested ordering policy, and provide managerial insights on the trade-offs. In addition, we extend the formulation to account for shipping delays and advanced order information.Singapore-MIT Alliance (SMA)
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Gimpl-Heersink, Lisa. "Joint pricing and inventory control under reference price effects." Thesis, 2008. http://epub.wu.ac.at/1913/1/document.pdf.
Full textAbstract:
In many firms the pricing and inventory control functions are separated. However, a number of theoretical models suggest a joint determination of inventory levels and prices, as prices also affect stocking risks. In this work, we address the problem of simultaneously determining a pricing and inventory replenishment strategy under reference price effects. This reference price effect models the empirically well established fact that consumers not only react sensitively to the current price, but also to deviations from a reference price formed on the basis of past purchases. The current price is then perceived as a discount or surcharge relative to this reference price. Thus, immediate effects of price reductions on profits have to be weighted against the resulting losses in future periods. We study how the additional dynamics of the consumers' willingness to pay affect an optimal pricing and inventory control model and whether a simple policy such as a base-stock-list-price policy holds in such a setting. For a one-period planning horizon we analytically prove the optimality of a base-stock-list-price policy with respect to the reference price under general conditions. We then extend this result to the two-period time horizon for the linear and loss-neutral demand function and to the multi-period case under even more restrictive assumptions. However, numerical simulations suggest that a base-stock-list-price policy is also optimal for the multi-period setting under more general conditions. We furthermore show by numerical investigations that the presence of reference price effects decreases the incentive for price discounts to deal with overstocked situations. Moreover, we find that the potential benefits from simultaneously determining optimal prices and stocking quantities compared to a sequential procedure can increase considerably, when reference price effects are included in the model. This makes an integration of pricing and inventory control with reference price effects by all means worth the effort. (author's abstract)
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Pavlovic, Radovan Thomas 1971. "Impact of variable emissions on ozone formation in the Houston area." 2009. http://hdl.handle.net/2152/11651.
Full textAbstract:
Ground level ozone is one of the most ubiquitous air pollutants in urban areas, and is generated by photochemical reactions of oxides of nitrogen (NOx) and volatile organic compounds (VOCs). The effectiveness of emission reduction strategies for ozone precursors is typically evaluated using gridded, photochemical air quality models. One of the underlying assumptions in these models is that industrial emissions are nearly constant, since many industrial facilities operate continuously at a constant rate of output. However, recent studies performed in the Houston-Galveston-Brazoria area indicate that some industrial emission sources exhibit high temporal emission variability that can lead to very rapid ozone formation, especially when emissions are composed of highly reactive volatile organic compounds. This work evaluates the impact of variable emissions from industrial sources on ground-level ozone formation in Houston area, utilizing a unique hourly emission inventory, known as the 2006 Special Inventory, created as a part of the second Texas Air Quality Study. Comparison of the hourly emissions inventory data with ambient measurements indicated that the impact of the variability of industrial source emissions on ozone can be significant. Photochemical modeling predictions showed that the variability in industrial emissions can lead to differences in local ozone concentrations of as much as 27 ppb at individual ozone monitor locations. The hourly emissions inventory revealed that industrial source emissions are highly variable in nature with diverse temporal patterns and stochastic behavior. Petrochemical and chemical manufacturing flares, which represent the majority of emissions in the 2006 Special Inventory, were grouped into categories based on industrial process, chemical composition of the flared gas, and the temporal patterns of their emissions. Stochastic models were developed for each categorization of flare emissions with the goal of simulating the characterized temporal emission variability. The stochastic models provide representative temporal profiles for flares in the petrochemical manufacturing and chemical manufacturing sectors, and as such serve as more comprehensive input for photochemical air quality modeling.text