Solution Approaches to Large-scale Production Scheduling Problems PDF Download

Author: Hoksung Yau
Publisher:
ISBN:
Category :
Languages : en
Pages : 126

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Author: Georgios M. Kopanos
Publisher: Springer
ISBN: 3030011836
Category : Technology & Engineering
Languages : en
Pages : 299

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Book Description
This book presents a number of efficient techniques for solving large-scale production scheduling and planning problems in process industries. The main content is supplemented by a wealth of illustrations, while case studies on large-scale industrial applications, ranging from continuous to semicontinuous and batch processes, round out the coverage. The book examines a variety of complex, real-world problems, and demonstrates solutions that are applicable to scenarios and countries around the world. Specifically, these case studies include: • the production planning of the bottling stage of a major brewery at the Cervecería Cuauhtémoc Moctezuma (Heineken Int) in Mexico;• the production scheduling for multi-stage semicontinuous processes at an ice-cream production facility of Unilever in the Netherlands;• the resource-constrained production planning for the yogurt production line at the KRI KRI dairy production facility in Greece; and• the production scheduling for large-scale, multi-stage batch processes at a pharmaceutical batch plant in Germany. In addition, the book includes industrial-inspired case studies of: • the simultaneous planning of production and logistics operations considering multi-site facilities for semicontinuous processes; and• the integrated planning of production and utility systems in process industries under uncertainty. Solving Large-scale Production Scheduling and Planning in the Process Industries offers a valuable reference guide for researchers and decision-makers alike, as it shows readers how to evaluate and improve existing installations, and how to design new ones. It is also well suited as a textbook for advanced courses on production scheduling and planning in industry, as it addresses the optimization of production and logistics operations in real-world process industries.

Author: Georgios Kopanos
Publisher:
ISBN:
Category :
Languages : en
Pages : 281

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Book Description
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.

Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 175

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Book Description
Optimization-based strategies to solve problems in production scheduling have been extensively used in the last decades due to their generality, flexibility and potential to find the best solutions in terms of costs, customer satisfaction, and efficiency. Traditionally, most efforts have been directed towards the development of mathematical models that are computationally tractable. However, the effective solution of large-scale scheduling models remains nontrivial. The main objective of this thesis is the development of solution methods for the different types of chemical plants. Our discussion is largely motivated by a new approach to the analysis of timing and inventory restrictions in scheduling problems. First, we propose a family of algorithms that are suitable for maximization problems in network environments. By preprocessing the original data we calculate parameters that are used to develop tightening constraints. We also introduce the concept of variable start and finish times and derive expressions to relate them and connect them with original decision variables. By means of computational experiments we show the effectiveness of these methods in improving the solution process of optimization-based models for scheduling. Second, we develop a new family of discrete-time models for sequential environments. Almost all the existing models in the literature use a continuous representation of time. We discuss the advantages of discrete-time models and propose different solution methods to improve their computational performance. A computational study is included to test the improvements and compare with existing approaches. Significant reduction in computational time and optimality gap is achieved. Third, we extend methods based on reformulations and tightening constraints from discrete-time to continuous time models in network environments. We use specific characteristics of the latter to improve computational performance, testing our methods on several benchmark instances. Finally we test the proposed methods on large-scale instances for which optimal solutions had not been found before or whose computational performances demanded long solution times. This way we show that our formulations and methods improve the tractability of industrial-scale instances. Optimal or near-optimal solutions are now accessible in reasonable time for many cases for which only suboptimal solutions from heuristics procedures or empirical methods were available.

Author: David Ray Anderson
Publisher:
ISBN:
Category :
Languages : en
Pages : 5

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Author: Bradimaarte
Publisher: CRC Press
ISBN: 9782884490207
Category : Mathematics
Languages : en
Pages : 364

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Book Description
Optimization techniques in production management are becoming increasingly important for efficient and competitive manufacturing. This book presents a collection of tutorial papers by outstanding researchers on the application of optimization concepts. Topics introduced include hierarchical production planning and large scale scheduling, optimal production control, exact and heuristic algorithms for production scheduling and stochastic modelling.

Author: Jeffrey W. Herrmann
Publisher: Springer Science & Business Media
ISBN: 0387331174
Category : Business & Economics
Languages : en
Pages : 331

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Book Description
This book concentrates on real-world production scheduling in factories and industrial settings. It includes industry case studies that use innovative techniques as well as academic research results that can be used to improve production scheduling. Its purpose is to present scheduling principles, advanced tools, and examples of innovative scheduling systems to persons who could use this information to improve their own production scheduling.

Author: Irfan M. Ovacik
Publisher: Springer Science & Business Media
ISBN: 1461563291
Category : Business & Economics
Languages : en
Pages : 217

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Book Description
The factory scheduling problem, that of allocating machines to competing jobs in manufacturing facilities to optimize or at least improve system performance, is encountered in many different manufacturing environments. Given the competitive pressures faced by many companies in today's rapidly changing global markets, improved factory scheduling should contribute to a flrm's success. However, even though an extensive body of research on scheduling models has been in existence for at least the last three decades, most of the techniques currently in use in industry are relatively simplistic, and have not made use of this body of knowledge. In this book we describe a systematic, long-term research effort aimed at developing effective scheduling algorithms for complex manufacturing facilities. We focus on a speciflc industrial context, that of semiconductor manufacturing, and try to combine knowledge of the physical production system with the methods and results of scheduling research to develop effective approximate solution procedures for these problems. The class of methods we suggest, decomposition methods, constitute a broad family of heuristic approaches to large, NP-hard scheduling problems which can be applied in other environments in addition to those studied in this book.

Author: Pierre Lopez
Publisher: John Wiley & Sons
ISBN: 1118624025
Category : Science
Languages : en
Pages : 284

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Book Description
The performance of an company depends both on its technological expertise and its managerial and organizational effectiveness. Production management is an important part of the process for manufacturing firms. The organization of production relies in general on the implementation of a certain number of basic functions, among which the scheduling function plays an essential role. This title presents recently developed methods for resolving scheduling issues. The basic concepts and the methods of production scheduling are introduced and advanced techniques are discussed, providing readers with a comprehensive and accessible guide to employing this process.

Author: Sudharshana Srinivasan
Publisher:
ISBN:
Category : Approximation algorithms
Languages : en
Pages : 138

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Book Description
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.