Relevant bibliographies by topics / Production planning and scheduling problem

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Production planning and scheduling problem'

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Published: 4 June 2021
Last updated: 8 February 2022

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Journal articles on the topic "Production planning and scheduling problem"

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Bhosale, Kailash Changdeorao, and Padmakar Jagannath Pawar. "Production planning and scheduling problem of continuous parallel lines with demand uncertainty and different production capacities." Journal of Computational Design and Engineering 7, no. 6 (July 14, 2020): 761–74. http://dx.doi.org/10.1093/jcde/qwaa055.

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Abstract Production planning and scheduling problems are highly interdependent as scheduling provides optimum allocation of resources and planning is an optimum utilization of these allocated resources to serve multiple customers. Researchers have solved production planning and scheduling problems by the sequential method. But, in this case, the solution obtained by the production planning problem may not be feasible for scheduling method. Hence, production planning and scheduling problems must be solved simultaneously. Therefore, in this work, a mathematical model is developed to integrate production planning and scheduling problems. The solution to this integrated planning and scheduling problem is attempted by using a discrete artificial bee colony (DABC) algorithm. To speed up the DABC algorithm, a k-means clustering algorithm is used in the initial population generation phase. This k-means clustering algorithm will help to converge the algorithm in lesser time. A real-life case study of a soap manufacturing industry is presented to demonstrate the effectiveness of the proposed approach. An objective function to minimize overall cost, which comprises the processing cost, material cost, utility cost, and changeover cost, is considered. The results obtained by using DABC algorithm are compared with those obtained by CPLEX software. There is a saving of ₹2 23 324 for weeks 1–4 in overall cost compared with the results obtained by using CPLEX software.
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Hassani, Zineb Ibn Majdoub, Abdellah El Barkany, Abdelouahhab Jabri, and Ikram El Abbassi. "Models for Solving Integrated Planning and Scheduling Problem: Computational Comparison." International Journal of Engineering Research in Africa 34 (January 2018): 161–70. http://dx.doi.org/10.4028/www.scientific.net/jera.34.161.

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This article concerns the integration of planning and scheduling production system. Planning and scheduling are usually treated separately because of their complexity. Scheduling largely depends on the production quantities computed at the production planning level. However, ignoring scheduling constraints in the tactical level leads to inconsistent decisions. So, it is important to integrate planning and scheduling to efficiently manage operations and to determine a realistic production plan for a given sequence of jobs on each machine. In this paper, we present some approaches proposed to solve the problem and we realize a comparison between the two most interesting ones, using the standard solver CPLEX.
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De Antón, J., J. Senovilla, J. M. González, and F. Acebes. "Production planning in 3D printing factories." International Journal of Production Management and Engineering 8, no. 2 (July 18, 2020): 75. http://dx.doi.org/10.4995/ijpme.2020.12944.

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<p>Production planning in 3D printing factories brings new challenges among which the scheduling of parts to be produced stands out. A main issue is to increase the efficiency of the plant and 3D printers productivity. Planning, scheduling, and nesting in 3D printing are recurrent problems in the search for new techniques to promote the development of this technology. In this work, we address the problem for the suppliers that have to schedule their daily production. This problem is part of the LONJA3D model, a managed 3D printing market where the parts ordered by the customers are reorganized into new batches so that suppliers can optimize their production capacity. In this paper, we propose a method derived from the design of combinatorial auctions to solve the nesting problem in 3D printing. First, we propose the use of a heuristic to create potential manufacturing batches. Then, we compute the expected return for each batch. The selected batch should generate the highest income. Several experiments have been tested to validate the process. This method is a first approach to the planning problem in 3D printing and further research is proposed to improve the procedure.</p>
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Stawowy, A., and J. Duda. "Coordinated Production Planning and Scheduling Problem in a Foundry." Archives of Foundry Engineering 17, no. 3 (September 1, 2017): 133–38. http://dx.doi.org/10.1515/afe-2017-0105.

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Abstract In the paper, we present a coordinated production planning and scheduling problem for three major shops in a typical alloy casting foundry, i.e. a melting shop, molding shop with automatic line and a core shop. The castings, prepared from different metal, have different weight and different number of cores. Although core preparation does not required as strict coordination with molding plan as metal preparation in furnaces, some cores may have limited shelf life, depending on the material used, or at least it is usually not the best organizational practice to prepare them long in advance. Core shop have limited capacity, so the cores for castings that require multiple cores should be prepared earlier. We present a mixed integer programming model for the coordinated production planning and scheduling problem of the shops. Then we propose a simple Lagrangian relaxation heuristic and evolutionary based heuristic to solve the coordinated problem. The applicability of the proposed solution in industrial practice is verified on large instances of the problem with the data simulating actual production parameters in one of the medium size foundry.
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Burkarda, Rainer E., Mihály Hujterb, Bettina Klinz, Rüdiger Rudolf, and Marc Wennink. "A process scheduling problem arising from chemical production planning." Optimization Methods and Software 10, no. 2 (January 1998): 175–96. http://dx.doi.org/10.1080/10556789808805710.

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Zhang, Zhi Cong, Kai Shun Hu, Hui Yu Huang, and Shuai Li. "Production Planning Considering Transfer Lot Size." Applied Mechanics and Materials 44-47 (December 2010): 552–56. http://dx.doi.org/10.4028/www.scientific.net/amm.44-47.552.

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Traditional methods conduct production planning and scheduling separately and solve transfer lot sizing problem between these two steps. Unfortunately, this may result in infeasibility in planning and scheduling. We take into account transfer lot size in production planning to obtain the consistency and to eliminate the gap between planning and real production. We present the detailed Transfer Lot-Based Model with mixed integer programming. Experiments show that performance measures of a production plan change remarkably with increasing of transfer lot size.
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Hassani, Zineb Ibn Majdoub, Abdellah El Barkany, Abdelouahhab Jabri, Ikram El Abbassi, and Abdel Moumen Darcherif. "New Approach to Integrate Planning and Scheduling of Production System: Heuristic Resolution." International Journal of Engineering Research in Africa 39 (November 2018): 156–69. http://dx.doi.org/10.4028/www.scientific.net/jera.39.156.

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In general, planning and scheduling of production are treated separately under the hierarchical strategy. Then, over the time, the iterative strategy appeared which partially considers the scheduling constraints during planning, except that the latter remains unsatisfactory because there is no guarantee that these constraints are taken into account. For this, is born the integrated strategy which integrates planning and scheduling and aims to solve the problem and define a feasible production plan. Since capacity constraints don’t reflect reality in terms of resource availability, and they are not always considered, capacity becomes aggregated. To remedy this problem, it is necessary to integrate more precise constraints of scheduling at the planning level. Based on this observation, we propose in this article a new model that integrates planning and scheduling and considers the constraint of resource availability. In our model, the objective function optimizes the total cost of production for a mono-level job-shop problem. To solve this N-P difficult problem we use a stochastic approached method as genetic algorithm (GA).
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Semenkina, O. E., and E. A. Popov. "Nature-Inspired Algorithms for Solving a Hierarchical Scheduling Problem in Short-Term Production Planning." Herald of the Bauman Moscow State Technical University. Series Instrument Engineering, no. 3 (126) (June 2019): 46–63. http://dx.doi.org/10.18698/0236-3933-2019-3-46-63.

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The paper deals with the scheduling problem relevant in many fields, such as project management, lesson scheduling or production scheduling. In practice, using optimisation methods to solve the scheduling problem is considerably restricted by the fact that in the real world, problem statement involves high dimensionality, high production process complexity and many nontrivial constraints. These specifics mean that even merely searching for a feasible solution becomes a difficult task. Consequently, in order to solve the problem in a reasonable amount of time it is necessary to use problem-oriented heuristics. Ensuring manufacturing process stability involves respecting all constraints, but at the same time, short-term production planning demands fast solutions whenever there is a change of state. We propose to implement a hierarchical problem structure that puts the travelling salesman problem at the top and replaces the nested resource-constrained project scheduling problem with a simulation model. The paper considers using such algorithms as the Lin --- Kernighan heuristic, the genetic algorithm and the ant colony optimization. We study the efficiency of employing the algorithms mentioned above to solve the scheduling problem in the statement proposed.
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Li, Ruiqiu, and Huimin Ma. "Integrating Preventive Maintenance Planning and Production Scheduling under Reentrant Job Shop." Mathematical Problems in Engineering 2017 (2017): 1–9. http://dx.doi.org/10.1155/2017/6758147.

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This paper focuses on a preventive maintenance plan and production scheduling problem under reentrant Job Shop in semiconductor production. Previous researches discussed production scheduling and preventive maintenance plan independently, especially on reentrant Job Shop. Due to reentrancy, reentrant Job Shop scheduling is more complex than the standard Job Shop which belongs to NP-hard problems. Reentrancy is a typical characteristic of semiconductor production. What is more, the equipment of semiconductor production is very expensive. Equipment failure will affect the normal production plan. It is necessary to maintain it regularly. So, we establish an integrated and optimal mathematical model. In this paper, we use the hybrid particle swarm optimization algorithm to solve the problem for it is highly nonlinear and discrete. The proposed model is evaluated through some simple simulation experiments and the results show that the model works better than the independent decision-making model in terms of minimizing maximum completion time.
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Tang, Peng, and Hong Bin Yu. "Planning and Scheduling Models for EMAS Productive Process." Applied Mechanics and Materials 365-366 (August 2013): 553–56. http://dx.doi.org/10.4028/www.scientific.net/amm.365-366.553.

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This paper addresses the problems of EMAS (an engineer material to arresting aircraft on the ground) production operation that the intensity of each product was uneven and cellular concrete was not completely crumple.In order to solve the problem the development of a nonlinear planning model for EMAS production was presented. The model is based on the company it could be helpful in guiding production. The second part of the work were optimization the model and get theoretical optimal value rely on both continuous and discrete time representations.
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Dissertations / Theses on the topic "Production planning and scheduling problem"

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Srinivasan, Sudharshana. "Spatial Scheduling Algorithms for Production Planning Problems." VCU Scholars Compass, 2014. http://scholarscompass.vcu.edu/etd/3406.

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Spatial resource allocation is an important consideration in shipbuilding and large-scale manufacturing industries. Spatial scheduling problems (SSP) involve the non-overlapping arrangement of jobs within a limited physical workspace such that some scheduling objective is optimized. Since jobs are heavy and occupy large areas, they cannot be moved once set up, requiring that the same contiguous units of space be assigned throughout the duration of their processing time. This adds an additional level of complexity to the general scheduling problem, due to which solving large instances of the problem becomes computationally intractable. The aim of this study is to gain a deeper understanding of the relationship between the spatial and temporal components of the problem. We exploit these acquired insights on problem characteristics to aid in devising solution procedures that perform well in practice. Much of the literature on SSP focuses on the objective of minimizing the makespan of the schedule. We concentrate our efforts towards the minimum sum of completion times objective and state several interesting results encountered in the pursuit of developing fast and reliable solution methods for this problem. Specifically, we develop mixed-integer programming models that identify groups of jobs (batches) that can be scheduled simultaneously. We identify scenarios where batching is useful and ones where batching jobs provides a solution with a worse objective function value. We present computational analysis on large instances and prove an approximation factor on the performance of this method, under certain conditions. We also provide greedy and list-scheduling heuristics for the problem and compare their objectives with the optimal solution. Based on the instances we tested for both batching and list-scheduling approaches, our assessment is that scheduling jobs similar in processing times within the same space yields good solutions. If processing times are sufficiently different, then grouping jobs together, although seemingly makes a more effective use of the space, does not necessarily result in a lower sum of completion times.
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Zhang, Luping, and 张路平. "Solving integrated process planning and scheduling problems with metaheuristics." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2014. http://hdl.handle.net/10722/208626.

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Process planning and scheduling are two important manufacturing planning functions which are closely related to each other. Usually, process planning and scheduling have to be performed sequentially, whereby the process plans are the input for scheduling. Many investigations have shown that the separate conduction of the two functions is much likely to ruin the effectiveness and feasibility of the process plans and schedules, and it is also difficult to cater for the occurrence of uncertainties in the dynamic manufacturing environment. The purpose of integrated process planning and scheduling (IPPS) is to perform the two functions concurrently. IPPS is a typical combinatorial optimization problem which belongs to the category of NP-hard problems. Research on IPPS has intensified in recent years. Researchers have reported various IPPS systems and solution approaches which are able to generate good solutions for specific IPPS problems. However, there is in general an absence of theoretical models for the IPPS problem representation, and research on the theoretical aspects of the IPPS is limited. The objective of this research is to establish a metaheuristic-based solution approach for the IPPS problem in flexible jobshop type of manufacturing systems. To begin with, a graph-based modeling approach for formulating the IPPS problem domain is proposed. This approach defines a way to use a category of AND/OR graphs to construct IPPS models. The graph-based IPPS model can be formulated using mathematical programming tools including polynomial mixed integer programming (PMIP) and mixed integer linear programming (MILP). The analytical mathematical programming approaches can be used to solve simple IPPS instances but they are not capable for large-scale IPPS problems. This research proposes a new IPPS modelling approach to incorporate metaheuristics in the solution strategy. Actually, the solution strategy comprises the metaheuristics and a mapping function. The metaheuristic is responsible for generating the operation sequences; a mapping function is then used to assign the operations to appropriate time slots on a schedule. General studies of applying constructive and improvement metaheuristics to solve the IPPS problem are conducted in this research. The ant colony optimization (ACO) is applied as a representative constructive metaheuristic, and a nonstandard genetic algorithm approach object-coding genetic algorithm (OCGA) is implemented as an improvement metaheuristic. The OCGA contains dedicated genetic operations to support the object-based genetic representation, and three particular mechanisms for population evolution. The metaheuristic-based solution approaches are implemented in a multi-agent system (MAS) platform. The hybrid MAS and metaheuristics based IPPS solution methodology is able to carry out dynamic rescheduling to cope with occurrence of uncertainties in practical manufacturing environments. Experiments have been carried out to test the IPPS solution approach proposed in this thesis. It is shown that both metaheuristics, ACO and OCGA, are having good performance in terms of solution quality and computational efficiency. In particular, due to the special genetic operations and population evolutionary mechanisms, the OCGA shows great advantages in experiments on benchmark problems. Finally, it is shown that the hybrid approach of MSA and metaheuristics is able to support real-time rescheduling in dynamic manufacturing systems.
published_or_final_version
Industrial and Manufacturing Systems Engineering
Doctoral
Doctor of Philosophy
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Zhai, Zhongping. "The Order Selection and Lot Sizing Problem in the Make-to-Order Environment." FIU Digital Commons, 2011. http://digitalcommons.fiu.edu/etd/364.

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This research is motivated by the need for considering lot sizing while accepting customer orders in a make-to-order (MTO) environment, in which each customer order must be delivered by its due date. Job shop is the typical operation model used in an MTO operation, where the production planner must make three concurrent decisions; they are order selection, lot size, and job schedule. These decisions are usually treated separately in the literature and are mostly led to heuristic solutions. The first phase of the study is focused on a formal definition of the problem. Mathematical programming techniques are applied to modeling this problem in terms of its objective, decision variables, and constraints. A commercial solver, CPLEX is applied to solve the resulting mixed-integer linear programming model with small instances to validate the mathematical formulation. The computational result shows it is not practical for solving problems of industrial size, using a commercial solver. The second phase of this study is focused on development of an effective solution approach to this problem of large scale. The proposed solution approach is an iterative process involving three sequential decision steps of order selection, lot sizing, and lot scheduling. A range of simple sequencing rules are identified for each of the three sub-problems. Using computer simulation as the tool, an experiment is designed to evaluate their performance against a set of system parameters. For order selection, the proposed weighted most profit rule performs the best. The shifting bottleneck and the earliest operation finish time both are the best scheduling rules. For lot sizing, the proposed minimum cost increase heuristic, based on the Dixon-Silver method performs the best, when the demand-to-capacity ratio at the bottleneck machine is high. The proposed minimum cost heuristic, based on the Wagner-Whitin algorithm is the best lot-sizing heuristic for shops of a low demand-to-capacity ratio. The proposed heuristic is applied to an industrial case to further evaluate its performance. The result shows it can improve an average of total profit by 16.62%. This research contributes to the production planning research community with a complete mathematical definition of the problem and an effective solution approach to solving the problem of industry scale.
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Summers, Deborah A. "Use of optimization models to solve labor planning and scheduling problems for the service industry." Thesis, Georgia Institute of Technology, 1998. http://hdl.handle.net/1853/24107.

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Rajagopalan, Sreekanth. "Design and Maintenance Planning Problems in Commodity Distribution and Chemical Site Networks." Research Showcase @ CMU, 2018. http://repository.cmu.edu/dissertations/1141.

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In this dissertation, we consider two specific types of problems over networks. In the first problem, we explore systematic methods to address some of the challenges in largescale maintenance planning in integrated chemical sites. In the second problem, we investigate different optimization model formulations for the design of flow distribution networks where the flow is potential-driven and nonlinearly related to the potential loss. Maintenance turnaround in the processing industry is a complex asset renewal project that includes huge capital expenditures and downtime losses. The option of deferring or rescheduling a turnaround project typically provides immediate financial relief from capital expenditure. However, the risk of running into site-wide disruptions in the form of unplanned events, yield, and reliability losses is not straightforward to assess. We propose mathematical optimization models to evaluate the risk of loss from turnaround deferrals in integrated sites and provide alternatives to reliably operate the site in a medium-term horizon. In the first chapter, we introduce the turnaround planning problem and the challenges it poses in integrated sites. We also introduce the background for the network design problem. In the second chapter, we study the financial impact of rescheduling turnarounds and the associated risk under unplanned outages. We compare the risk profiles presented by different production planning strategies. We propose a stochastic programming model for production planning that optimally builds up inventory ahead of time to hedge against production losses during unplanned outages. In the third chapter, we extend the stochastic optimization to handle a large set of scenarios and propose a Lagrangean decomposition method that improves a myopic production plan. The fourth chapter proposes a mixed-integer linear programming model that prescribes turnaround schedules when the underlying assets undergo yield loses and selectivity degradation. Here, we also study the impact of deferrals over a long-term horizon. The penultimate chapter addresses the nonlinear network design problem.The closing chapter summarizes the work and provides a few future directions. In the spirit of advancing manufacturing paradigms, the thesis supports investment in modeling efforts that address enterprise-wide planning problems.
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Xu, Chaojun [Verfasser]. "Coordination and Decomposition of Large-Scale Planning and Scheduling Problems with Application to Steel Production / Chaojun Xu." Aachen : Shaker, 2013. http://d-nb.info/1049381610/34.

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Kopanos, Georgios. "Techniques for the efficient solution of Large-scale production scheduling & planning problems in the process industries." Doctoral thesis, Universitat Politècnica de Catalunya, 2011. http://hdl.handle.net/10803/109962.

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Nowadays, every company seeks to optimize its Supply Chain (SC) in response to competitive pressures or to acquire advantage of new flexibility in the restrictions on world trade. The process systems engineering research community has been aware of this change and is playing a key role in expanding the system boundaries from chemical process systems to business process systems. The global optimization of a SC network is an extremely complex task. For this reason, SC decisions are typically divided into three decision levels: the operational (scheduling), the tactical (planning), and the strategic (design). Since most academic developments are too distant from industrial environments, the aim of this thesis is to be a step forward in narrowing the gap between planning and scheduling theory and practice by devising efficient mathematical approaches for solving real-life industrial scheduling and planning problems. An overview of production planning and scheduling, an analysis of existing approaches, methods and tools used throughout this study are first presented. The second part of this thesis is focused on the development of mathematical models for production processes with continuous parallel units. In this part, a novel mathematical programming framework is developed based on elegant modeling of the underlying problem. This work addresses challenging problems in a highly complex real-life bottling facility. The proposed framework addresses appropriately important changeover aspects such as changeover carryover and crossover, thereby leading to solutions with resulting in higher utilization of resources. The third part is focused on semicontinuous industries, which combine continuous and batch operation modes. First, a mathematical programming framework and a solution strategy are presented for the optimal production scheduling of multiproduct multistage semicontinuous process industries. A problem in an ice-cream production line has been considered; and it has been successfully solved. Second, a general mathematical programming approach is developed for the resource-constrained production planning problem in semicontinuous processes. This work has been motivated by a challenging problem in food processing industries related to yogurt production lines, where labor constitutes the limited resource constraint. Third, a novel mathematical formulation for the simultaneous optimization of production and logistics operations planning in large-scale single- or multi-site semicontinuous process industries is proposed. Alternative transportation modes are considered. Two industrial-size case studies for a real-life dairy industry have been solved. The forth part of the thesis deals with scheduling in batch processes. First, a real-life multiproduct multistage pharmaceuticals production facility is considered. A systematic two-stage iterative solution strategy, based on mathematical programming, has been developed to address this problem. Additionally, a new precedence concept have been developed in order to cope with objectives containing changeover issues. A salient feature of the proposed approach is that the scheduler can maintain the number of decisions at a reasonable level, thus reducing the solution search space. This often ensures a more stable and predictable optimization model behavior. Finally, a preliminary two-layered decomposition method to the batch process scheduling problem in multipurpose production plants is developed. The procedure is tested on several instances of a benchmark scheduling problem that considers a polymers production plant.
Hoy en día, debido a que las condiciones económicas y políticas cambian rápidamente, las empresas globales se enfrentan a un desafío continuo para reevaluar constantemente y configurar de forma óptima las operaciones de su cadena de suministro (CS) para alcanzar los índices de rendimiento clave, tales como la reducción de costes de rentabilidad y servicio al cliente. Las empresas buscan optimizar sus CSs en respuesta a presiones de la competencia o para adquirir ventaja de una mayor flexibilidad en las restricciones sobre todo en el comercio mundial. Las industrias de proceso también siguen esta tendencia. La comunidad que investiga la ingeniería de los sistemas de procesos ha sido consciente de este cambio y, hoy en día, está jugando un papel clave en la expansión de los límites de los sistemas más allá de los procesos químicos para incluir también los sistemas de negocio. La optimización global de una red CS es una tarea extremadamente compleja. Por esta razón, las decisiones CS por lo general contemplan tres niveles de decisión: operativo (programación de operaciones), táctico (planificación de la producción) y estratégico (diseño). La planificación de la producción y la programación de operaciones constituyen una parte crucial de los niveles de decisión jerarquizados de la CS completa. Las actividades de planificación y programación tratan de la asignación en el tiempo de los recursos escasos entre actividades que compiten para satisfacer de forma eficiente dichas necesidades. Más concretamente, la función de planificación tiene como objetivo optimizar el rendimiento económico de la empresa, ya que debe hacer coincidir la producción con la demanda de la mejor manera posible. El componente de programación de la producción es de vital importancia ya que es la capa que traduce los imperativos económicos del plan en una secuencia de acciones a ser ejecutadas en la planta, con el fin de ofrecer el rendimiento económico optimizado previsto por el plan de alto nivel. En general, las investigaciones recientes se dirigen a la búsqueda de soluciones que permitan un manejo eficiente y preciso de problemas de gran tamaño y de complejidad cada vez mayor. Sin embargo, queda mucho trabajo por hacer tanto en las mejoras del modelo como en las mejoras en los algoritmos de solución del problema, cuando se trata de abordar de manera rutinaria problemas relevantes para la industria, donde el software producido debe ser utilizado de manera regular por los profesionales en el campo. Además, los nuevos desarrollos académicos son en su mayoría de cierta complejidad, pero relativamente de pequeño tamaño comparados con los problemas industriales incluso de mediano tamaño. Por lo tanto, la aplicación de nuevas estrategias de producción y nuevos enfoques de programación en los estudios industriales en la vida real constituye un reto difícil. Como la mayoría de los desarrollos académicos están demasiado lejos del entorno de aplicabilidad industrial, el objetivo de esta tesis es dar un paso significativo en la reducción del salto existente entre la teoría y la práctica de la planificación y programación mediante la elaboración de enfoques eficaces de programación matemática para la solución
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Moussavi, Seyed Esmaeil. "Workforce scheduling and job rotation by considering ergonomic factors (Presentation of the Sequencing Generalized Assignment Problem) : application to production and home healthcare systems." Thesis, Bourgogne Franche-Comté, 2018. http://www.theses.fr/2018UBFCA017/document.

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Cette thèse porte sur la planification du personnel en accordant une attention particulière à l'aspect humain et aux facteurs ergonomiques dans le domaine de la production. Un certain nombre de modèles mathématiques sont présentés pour formuler les problèmes d'ordonnancement et de planification du personnel étudié. Concernant les modèles de planification, la productivité du système de fabrication et le bien-être des travailleurs sont ciblés. De cette manière, une méthode d'affectation des travailleurs est présentée pour réduire le temps de production et une méthode d'ordonnancement pour la rotation des tâches est présentée afin d’équilibrer la charge de travail des opérateurs. À cet effet, une analyse ergonomique est effectuée sur les postes de travail du système de production étudié. Cette analyse aboutit à l'évaluation des postes du travail suivant la convention dite des feux de circulation, c'est-à-dire que les postes sont classés dans les niveaux de charge faible, moyen et élevé qui sont représentés respectivement par les couleurs verte, jaune et rouge. Une approche mathématique est développée pour convertir ces résultats en valeurs numériques, car les paramètres quantitatifs sont plus applicables pour l'optimisation de la planification. Une programmation multi-objectifs est proposée pour optimiser les deux objectifs mentionnés du problème d'ordonnancement de tournée du personnel étudié. Les méthodes d'agrégation linéaire et de ε-contrainte sont appliquées pour résoudre ce modèle d'optimisation. En outre, cette thèse présente une nouvelle variante du problème d'affectation appelé problème d'affectation généralisée par séquence qui est défini pour la planification du personnel dans un système combiné constitué des postes de travail en série et en parallèle. Il est prouvé que ce problème d'optimisation combinatoire est NP-difficile et les méthodes exactes ne sont pas capables de résoudre les instances de grande taille. Ainsi, trois méthodes approchées composées de deux approches matheuristiques et une heuristique hybride sont développées pour résoudre ce problème. Les méthodes matheuristiques sont basées sur la décomposition de la formulation pour simplifier le modèle principal en deux ou plusieurs modèles plus petits. La troisième méthode est une heuristique gloutonne combinée à une recherche locale. En outre, dans la dernière étape de cette thèse, la planification des ressources humaines pour un système de soins à domicile est formulée mathématiquement. Selon la structure du système, une intégration des problèmes d'affectation et de tournées de véhicules est présentée. Enfin, une approche matheuristique en trois étapes est proposée pour résoudre ce problème d'optimisation combinatoire
This thesis concerns the human resource planning by paying a special attention to the human aspect and ergonomic factors in the manufacturing domain. A number of mathematical models are presented to formulate the studied workforce scheduling and planning problems. In the planning models, the productivity of the manufacturing system and the well-being of the workers are targeted. In this way, a worker assignment approach is presented to reduce the production time and a job rotation scheduling approach is presented to balance the workloads on the operators. For this purpose, an ergonomic analysis is carried out on the jobs of the studied production system. This analysis results in the traffic light evaluation for the jobs, i.e., the jobs are categorized into the low, medium and high workload levels which are presented respectively by the green, yellow and red colors. A mathematical approach is developed to convert these outputs to the numerical values, because the quantitative parameters are more applicable for the optimization of the planning. A multi-objective programming is proposed to optimize two mentioned objectives of the studied workforce scheduling problem. Both linear aggregation and epsilon-constraint methods are applied to solve this optimization model. Furthermore, this thesis presents a novel variant of the assignment problem called sequencing generalized assignment problem which is defined for workforce scheduling in a combined system consisting of the jobs in series and in parallel. It is proved that this combinatorial optimization problem is NP-hard and the exact methods are not able to solve the large-scale instances. Hence, three approximate methods consisting of two matheuristic and a hybrid heuristic approaches are developed to solve it. The matheuristic methods are based on the decomposition of the formulation to break down and simplify the main model into two or more smaller models. The third method is a greedy heuristic combined with a local search. The efficiency of the three mentioned methods is evaluated by various instances of different sizes. Moreover, in the last step of this thesis, the human resource planning for a home healthcare system is formulated mathematically. According to the structure of the system, an integration of the worker assignment and vehicle routing problems is presented. Finally, a three-steps matheuristic approach is proposed to solve this combinatorial optimization problem
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Turatti, Rangel. "Solução de problemas complexos de programação através de regras desenvolvidas em tecnologia APS." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2010. http://hdl.handle.net/10183/35618.

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O ambiente competitivo no qual as empresas estão inseridas é caracterizado por mudanças frequentes na demanda de seus produtos e por uma necessidade em reduzir custos. Para obter sucesso frente à concorrência, se faz necessário alcançar resultados através da melhoria do processo produtivo, oferecendo respostas mais rápidas a variações na demanda e com uma utilização adequada dos recursos produtivos. Neste contexto, a utilização de softwares Advanced Planning and Scheduling com regra personalizada de programação possibilita melhoria no planejamento e programação da empresa no sentido dos objetivos citados. A partir disso, este trabalho propõe uma sistemática de desenvolvimento e implantação de regras de programação personalizadas. Após, é apresentada aplicação de um caso prático no qual foram detalhadas todas as etapas propostas na sistemática, desde o entendimento das necessidades da empresa até a avaliação dos resultados obtidos.
The competitive environment in which firms operate is characterized by frequent changes in product demand and a necessity to reduce costs. To succeed against the competition, it is necessary to gain competitive advantage by improving the production process, providing faster responses to changes in demand and proper use of productive resources. In this context, the use of Advanced Planning and Scheduling software with custom programming rule allows improved planning and programming company towards the objectives mentioned. This study proposes a systematic development and deployment of custom programming rules, next it is presented a case study which detail the stages proposed in the systematic, from the understanding of the business requirement until the evaluation of results.
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Martínez, Karim Yaneth Pérez. "Planejamento e programação da produção na indústria de embalagens em polpa moldada." Universidade Federal de São Carlos, 2013. https://repositorio.ufscar.br/handle/ufscar/3827.

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This research deals with the production planning and scheduling problem in the molded pulp packing industry, studying particularly a plant of molded pulp packages for eggs. The production process can be subdivided into two processes: molding process and printing process. The main challenge for production planning activities is on the molding process, where products are produced through tooling that have several molds. These tooling are called "Molding Patterns" or " Conformation Patterns". Each one of the molding patterns can contain one, two, until three kind of molds, allowing to produce several products simultaneously. Producing several products at the time can generate large inventory for low demand products and also null inventory for high demand products. Thus, different inventory levels are defined for each product based on their demand behavior, in order to control inventory quantities. In this way, decisions related to the production planning and scheduling in this production process involve deciding which molding patterns should used, how much time they should be used, and how they should be sequenced. All these should be make taking into account a parallel machine system and sequenced-dependent setups time and costs, in order to minimize inventory and setups costs, as well as penalties associated to inventory out of the specified inventory levels of each product. To represent this problem we proposed two formulations: the first one based on the Capacitated Lot Sizing and Scheduling Problem (CLSP), and the second one based on the General Lot Sizing and Scheduling Problem (GLSP). The results from the models were compared in a set of real word instances of a plant, in order to check the adequacy to represent the decisions involved in the studied production process, as well as the main differences between their production plans and performance of the models. The proposed formulations were also adapted for a particular instance, in order to compare their productions plans against the production plan implement by the studied plant. Results show that the proposed models represent rightly decisions involved in the production planning and scheduling in the molded pulp. Furthermore, the solutions obtained by the proposed models represent production plans with costs significantly lower than the schedule implemented by a real plant in this kind of industry.
Este trabalho aborda o problema de planejamento e programação da produção na indústria de embalagens em polpa moldada, considerando particularmente uma fábrica de embalagens para acondicionamento de ovos. O processo de produção pode ser subdividido em dois processos: processo de moldagem e processo de estampagem. O principal desafio para as atividades de planejamento encontra-se no processo de moldagem, em que a obtenção dos produtos depende da utilização de diferentes ferramentais, formados por um conjunto de moldes. Estes ferramentais são chamados de padrões de conformação ou padrões de moldagem , e podem conter um, dois ou até três tipos de moldes, permitindo a produção simultânea de produtos diferentes. Esta produção simultânea de itens pode gerar grandes níveis de estoque de produtos de baixa demanda e estoques nulos para produtos de alta demanda, desta forma, são definidos diferentes níveis de estoque para cada produto com base no comportamento da sua demanda. As decisões envolvidas no planejamento e programação da produção neste tipo de processo envolve a escolha dos padrões de moldagem a serem utilizados, o tempo de produção de cada padrão, e a sequência em que estes devem ser programados, considerando um sistema de linhas paralelas idênticas e tempos e custos de preparação dependentes da sequência. Estas decisões devem ser definidas de modo a minimizar os custos de estocagem, preparação, e penalidades associadas ao desvio do volume do estoque em relação aos níveis estabelecidos para cada produto. Para representar o problema são propostas dois tipos de formulações: a primeira baseada no Problema de Dimensionamento de Lotes Capacitado (CLSP), e a segunda baseada no Problema de Dimensionamento e Sequenciamento de Lotes Geral (GLSP). Os resultados da resolução dos modelos são comparados com base em exemplares reais da fábrica em estudo, a fim de verificar sua adequação para representar as decisões envolvidas no sistema de produção, as principais diferenças nos planos de produção gerados, e o desempenho destes modelos. Os resultados obtidos demonstram que os modelos propostos representam adequadamente as decisões no sistema de produção estudado, e geram planos de produção significativamente melhores que os planos praticados pela fábrica.
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Books on the topic "Production planning and scheduling problem"

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Shiroma, Patricia Jay. Efficient Production Planning and Scheduling. Wiesbaden: Deutscher Universitätsverlag, 1996. http://dx.doi.org/10.1007/978-3-663-08438-9.

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Construction planning and scheduling. 4th ed. Upper Saddle River, N.J: Pearson Prentice Hall, 2012.

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Gessner, Robert A. Master production schedule planning. New York: Wiley, 1986.

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Hermann, Jeffrey W. Handbook of production scheduling. New York: Springer, 2006.

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Lotsizing and scheduling for production planning. Berlin: Springer-Verlag, 1994.

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Haase, Knut. Lotsizing and Scheduling for Production Planning. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/978-3-642-45735-7.

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Hinze, Jimmie. Construction planning and scheduling. 2nd ed. Upper Saddle River, N.J: Pearson/Prentice Hall, 2004.

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Construction planning and scheduling. Upper Saddle River, N.J: Prentice Hall, 1998.

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Palmer, Doc. Maintenance planning and scheduling handbook. New York: McGraew-Hill, 1999.

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Maintenance planning and scheduling handbook. 2nd ed. New York: McGraw-Hill, 2006.

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Book chapters on the topic "Production planning and scheduling problem"

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Voß, Stefan. "The Two — Stage Hybrid — Flowshop Scheduling Problem with Sequence — Dependent Setup Times." In Operations Research in Production Planning and Control, 336–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-78063-9_21.

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Man, K. F., K. S. Tang, and S. Kwong. "Genetic Algorithms in Production Planning and Scheduling Problems." In Advanced Textbooks in Control and Signal Processing, 259–80. London: Springer London, 1999. http://dx.doi.org/10.1007/978-1-4471-0577-0_9.

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Kunapareddy, Aditya, and Gopichand Allaka. "An Improved Genetic Algorithm for Production Planning and Scheduling Optimization Problem." In Intelligent Manufacturing and Energy Sustainability, 157–71. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-1616-0_15.

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Jélvez, E., N. Morales, and P. Nancel-Penard. "Open-Pit Mine Production Scheduling: Improvements to MineLib Library Problems." In Proceedings of the 27th International Symposium on Mine Planning and Equipment Selection - MPES 2018, 223–32. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-99220-4_18.

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Moosavi, Ehsan. "Modeling Long-Term Production Scheduling Problem and Its Solution Using a Bat Meta-heuristic Method." In Proceedings of the 28th International Symposium on Mine Planning and Equipment Selection - MPES 2019, 111–19. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33954-8_13.

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Htwe, Daniel. "Solving Complex Mine Optimisation Problems Using Blend Vectoring and Multi-objective Production Scheduling." In Proceedings of the 28th International Symposium on Mine Planning and Equipment Selection - MPES 2019, 51–66. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-33954-8_6.

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Stadtler, Hartmut. "Production Planning & Scheduling." In Supply Chain Management und Advanced Planning, 231–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-14131-7_11.

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Stadtler, Hartmut. "Production Planning and Scheduling." In Supply Chain Management and Advanced Planning, 177–93. Berlin, Heidelberg: Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/978-3-662-10142-1_11.

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Stadtler, Hartmut. "Production Planning and Scheduling." In Supply Chain Management and Advanced Planning, 149–65. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-662-04215-1_10.

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Stadtler, Hartmut. "Production Planning and Scheduling." In Springer Texts in Business and Economics, 195–211. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-55309-7_10.

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Conference papers on the topic "Production planning and scheduling problem"

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Kovalyov, Mikhail Y., Xavier Delorme, and Alexandre Dolgui. "Workforce planning for cyclic production of multiple parts." In Workshop on dynamic scheduling problems. Polish Mathematical Society, 2016. http://dx.doi.org/10.14708/isbn.978-83-937220-7-p47-50.

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Kovalyov, Mikhail Y., Xavier Delorme, and Alexandre Dolgui. "Workforce planning for cyclic production of multiple parts." In Workshop on dynamic scheduling problems. Polish Mathematical Society, 2016. http://dx.doi.org/10.14708/isbn.978-83-937220-7-5p47-50.

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Herrmann, Jeffrey W., Mark Fleischer, Edward Lin, Vidit Mathur, and Jim Glasser. "Affordable Space Systems Manufacturing: Intelligent Synthesis Technology, Process Planning, and Production Scheduling." In ASME 2001 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/detc2001/cie-21281.

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Abstract Low volume production associated with space systems manufacturing is inherently expensive, time-consuming, and risk-laden. At the root of this problem is an inability to adequately predict, monitor, and control the product development and sustainment process. This paper describes the ASSIST system, an intelligent knowledge management system designed to address inefficient information management processes and improve space system affordability. ASSIST is designed for collaborative engineering, manufacturing, and testing within a company, between companies, and between local and remote individuals. ASSIST uses web-based standards (including HTTP and XML) as the common message approach connecting its components. Automated process planning and production scheduling is a key component of ASSIST. This paper describes an integrated process planning and production scheduling problem and discusses the solution approach.
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Sadeh, Norman M., David W. Hildum, Stephen F. Smith, Dag Kjenstad, Thomas J. Laliberty, and John McA’Nulty. "Integration of Process Planning and Production Scheduling for Agile Manufacturing: A Case Study." In ASME 1997 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1997. http://dx.doi.org/10.1115/detc97/dfm-4330.

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Abstract As companies increasingly customize their products, move towards smaller lot production and experiment with more flexible customer/supplier arrangements, such as those made possible by Electronic Data Interchange (EDI), they increasingly require the ability to (1) respond quickly, accurately and competitively to customer requests for bids on new products and (2) efficiently work out supplier/subcontractor arrangements for these new products. This in turn requires the ability to (1) rapidly convert standard-based product specifications into process plans and (2) quickly integrate process plans for new orders into the existing production schedule to best accommodate the current state of the manufacturing enterprise. This paper describes IP3S, an Integrated Process Planning/Production Scheduling shell for agile manufacturing. IP3S utilizes a blackboard architecture that supports (1) concurrent development and dynamic revision of integrated process planning/production scheduling solutions, (2) maintenance of multiple problem instances and solutions, (3) flexible user-oriented decision making, (4) declarative representation of control information, (5) the use of a common representation for exchanging information, (6) coordination with outside information sources and (7) portability and ease of integration with legacy systems. IP3S has been validated in the context of a large and highly dynamic machine shop at Raytheon’s Andover manufacturing facility. Empirical results show an average performance improvement of 23% in solution quality over a decoupled approach to building process planning/production scheduling solutions.
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Ying, Liu,. "An Optimal Integrated Production Planning and Scheduling Method for Bell-Type Anneal Shop." In Information Control Problems in Manufacturing, edited by Bakhtadze, Natalia, chair Dolgui, Alexandre and Bakhtadze, Natalia. Elsevier, 2009. http://dx.doi.org/10.3182/20090603-3-ru-2001.00132.

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He, Guoxi, Yongtu Liang, Limin Fang, Qi Zheng, and Liying Sun. "Optimization of Planning and Scheduling of Refinery Product Based on Downstream Requirements." In 2016 11th International Pipeline Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/ipc2016-64150.

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The disconnect between the optimization systems of upstream production and downstream demand poses a legitimate problem for China’s refined oil industry in terms of overproduction waste. Established methods only partially model the refinery system and are unable to integrate detailed production plans or meet market demands. Therefore, the research on production scheduling optimization combined with the demand of downstream pipeline network has very real applications that not only reduce the consumption of human/material resources, but also increase economic efficiency. This paper aims to optimize the production scheduling of refined oil transportation based on the demand of downstream product pipelines by analyzing the relationships between crude oil supply, refinery facility capacities and refinery tanks storage. The new model will minimize the refined production surplus therefore minimizing refinery costs and wastage. This is done by implementing models custom designed to optimize the three subsystems of the overall process: oil product blending scheduling optimization, producing and processing equipment scheduling optimization, and mixed crude oil scheduling optimization. We first analyzed the relationship between all the production units from the crude oil to the distributional destinations of oil products. A mathematical model of the refinery production scheduling was then built with minimum total surplus inventory as the objective function. We assumed a known downstream demand and used a step by step model to optimize oil stocks. The oil blending plan, production scheduling, amount of crude oil, and refined oil mixing ratios were all derived from the model using three methods: a nonlinear method called Particle Swarm Optimization (PSO), the simplex method and the enumeration method. The evidence laid out in this paper verifies our models functionality and suggests that systems can be significantly optimized by using these methods which can provide solutions for industries with similar challenges. Optimization of the refinery’s overall production process is achieved by implementing models for each of the three distinguished subsystems: oil blending model, plant scheduling model, and the mixed crude oil refining model. The demand dictates the final production quantities. From those figures we are able to place constraining limits on the input crude oil. The refined oil production scheme is continuously enhanced by determining the amount of constituent feed on the production equipment according to the results of previous production cycle. After optimization, the minimum surplus inventory of the five oil components approach their lower limits that were calculated using our models. We compare the literature on scheduling optimization challenges both in China and abroad while providing a detailed discussion of the present situation of Chinese refineries. The interrelationships of production processes on each other are revealed by analyzing the system and breaking it down to three fundamental parts. Basing the final production predictions on the downstream demand, we are able to achieve a minimum refinery surplus inventory by utilizing a comprehensive refinery scheduling model composed of three sub-models.
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Kawaguchi, Shuhei, and Yoshikazu Fukuyama. "Parallel Hybrid Particle Swarm Optimization for Integration Framework of Optimal Operational Planning Problem of an Energy Plant and Production Scheduling Problem." In 2019 International Conference on Artificial Intelligence in Information and Communication (ICAIIC). IEEE, 2019. http://dx.doi.org/10.1109/icaiic.2019.8669080.

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Tolio, Tullio, Marcello Urgo, and Arianna Alfieri. "Production and Material Requirements Planning in Manufacturing-to-Order Environments: An Application to Machining Centers Production." In ASME 2008 9th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2008. http://dx.doi.org/10.1115/esda2008-59421.

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Long and medium-term production planning are tools to match production orders and resources capability but can also be used as baseline for material procurement. In some systems, however, to reduce the complexity of the planning problem, distinct production operations are aggregated into activities which normally represent production phases. This is the case of some Manufacturing-to-Order and Engineering-to-Order Systems. The lack of a detailed schedule of the manufacturing operations can cause difficulties in providing a proper Material Requirements Planning and can affect the feasibility of the production plan. The paper proposes an approach to extract scheduling information from a production plan, grounding on the knowledge of the production process, to support material procurement. Once a criterion to aggregate operations is chosen and the plan devised, the description of production operations and their precedence relations are used to obtain temporal ranges for production operations and, hence, deadline ranges are provided for the MRP. The proposed approach is applied to an industrial environment producing machining centers.
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Oh, Yosep, Chi Zhou, and Sara Behdad. "Production Planning for Mass Customization in Additive Manufacturing: Build Orientation Determination, 2D Packing and Scheduling." In ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/detc2018-85639.

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The efficient production planning of Additively Manufactured (AM) parts is a key point for industry-scale adoption of AM. This study develops an AM-based production plan for the case of manufacturing a significant number of parts with different shapes and sizes by multiple machines with the ultimate purpose of reducing the cycle time. The proposed AM-based production planning includes three main steps: (1) determination of build orientation; (2) 2D packing of parts within the limited workspace of AM machines; and (3) scheduling parts on multiple AM machines. For making decision about build orientation, two main policies are considered: (1) laying policy in which the focus is on reducing the height of parts; and (2) standing policy which aims at minimizing the projection area on the tray to reduce the number of jobs. A heuristic algorithm is suggested to solve 2D packing and scheduling problems. A numerical example is conducted to identify which policy is more preferred in terms of cycle time. As a result, the standing policy is more preferred than the laying policy as the number of parts increases. In the case of testing 3,000 parts, the cycle time of standing policy is about 6% shorter than laying policy.
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Shen, Weiming, and Qi Hao. "Agent-Based Dynamic Manufacturing Scheduling." In ASME 2006 International Manufacturing Science and Engineering Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/msec2006-21111.

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Manufacturing enterprises are facing a major challenge to improve their production efficiency in order to survive in a globally competitive market. There is an opportunity to develop and apply intelligent scheduling software tools to improve their productivity and profitability. We have developed a distributed dynamic manufacturing scheduling technology using intelligent software agents. This technology can well address dynamic changes and disturbances in the shop floor locally without disruptions to regular production — a problem that cannot be solved by traditional planning and scheduling systems because these changes and disturbances cannot be predicted in advance. It can significantly improve equipment utilization rates thereby improving the efficiency and productivity of manufacturing enterprises. We have developed software prototype systems within our research facilities. We are collaborating with industrial partners to validate the technology in industrial settings and are looking for a software company in the manufacturing sector to commercialize the technology.
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Reports on the topic "Production planning and scheduling problem"

1

Jarvis, James P., and Melissa R. Bowers. Hierarchical Production Planning and Scheduling in the Apparel Industry. Fort Belvoir, VA: Defense Technical Information Center, June 1995. http://dx.doi.org/10.21236/ada298601.

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Sadeh, Norman M., Thomas J. Laliberty, Robert V. Bryant, and Stephen F. Smith. Development of an Integrated Process Planning/Production Scheduling Shell for Agile Manufacturing. Fort Belvoir, VA: Defense Technical Information Center, November 1995. http://dx.doi.org/10.21236/ada310806.

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