Cover image for Scheduling in Supply Chains Using Mixed Integer Programming.
Scheduling in Supply Chains Using Mixed Integer Programming.
Title:
Scheduling in Supply Chains Using Mixed Integer Programming.
Author:
Sawik, Tadeusz.
ISBN:
9781118029091
Personal Author:
Edition:
1st ed.
Physical Description:
1 online resource (494 pages)
Contents:
Scheduling in Supply Chains Using Mixed Integer Programming -- Contents -- List of Figures -- List of Tables -- Preface -- Acknowledgments -- Introduction -- Part One Short-Term Scheduling in Supply Chains -- 1. Scheduling of Flexible Flow Shops -- 1.1 Introduction -- 1.2 Mixed Integer Programs for Scheduling Flow Shops -- 1.3 Constructive Heuristics for Scheduling Flexible Flow Shops -- 1.4 Scheduling Flow Shops with Limited Machine Availability -- 1.5 Computational Examples -- 1.6 Comments -- Exercises -- 2. Scheduling of Surface Mount Technology Lines -- 2.1 Introduction -- 2.2 SMT Line Configurations -- 2.3 General Scheduling of SMT Lines -- 2.4 Batch Scheduling of SMT Lines -- 2.5 An Improvement Heuristic for Scheduling SMT Lines -- 2.6 Computational Examples -- 2.7 Comments -- Exercises -- 3. Balancing and Scheduling of Flexible Assembly Lines -- 3.1 Introduction -- 3.2 Balancing and Scheduling of Flexible Assembly Lines with Infinite In-Process Buffers -- 3.3 Balancing and Scheduling of SMT Lines -- 3.4 Comments -- Exercises -- 4. Loading and Scheduling of Flexible Assembly Systems -- 4.1 Introduction -- 4.2 Loading and Scheduling of Flexible Assembly Systems with Single Stations and Infinite In-Process Buffers -- 4.3 Loading and Scheduling of Flexible Assembly Systems with Parallel Stations and Finite In-Process Buffers -- 4.4 Comments -- Exercises -- Part Two Medium-Term Scheduling in Supply Chains -- 5. Customer Order Acceptance and Due Date Setting in Make-to-Order Manufacturing -- 5.1 Introduction -- 5.2 Problem Description -- 5.3 Bi-Objective Order Acceptance and Due Date Setting -- 5.4 Lexicographic Approach -- 5.5 Scheduling of Customer Orders -- 5.6 Computational Examples -- 5.7 Comments -- Exercises -- 6. Aggregate Production Scheduling in Make-to-Order Manufacturing -- 6.1 Introduction -- 6.2 Problem Description.

6.3 Bi-Objective Scheduling of Customer Orders -- 6.4 Multi-Objective Scheduling of Customer Orders -- 6.5 Scheduling of Single-Period Customer Orders -- 6.6 Comments -- Exercises -- 7. Reactive Aggregate Production Scheduling in Make-to-Order Manufacturing -- 7.1 Introduction -- 7.2 Problem Description -- 7.3 Mixed Integer Programs for Reactive Scheduling -- 7.4 Rescheduling Algorithms -- 7.5 Input and Output Inventory -- 7.6 Computational Examples -- 7.7 Comments -- Exercises -- 8. Scheduling of Material Supplies in Make-to-Order Manufacturing -- 8.1 Introduction -- 8.2 Flexible vs. Cyclic Material Supplies -- 8.3 Model Enhancements -- 8.4 Computational Examples -- 8.5 Comments -- Exercises -- 9. Selection of Static Supply Portfolio in Supply Chains with Risks -- 9.1 Introduction -- 9.2 Selection of a Supply Portfolio without Discount under Operational Risks -- 9.3 Selection of Supply Portfolio with Discount under Operational Risks -- 9.4 Computational Examples -- 9.5 Selection of Supply Portfolio under Disruption Risks -- 9.6 Single-Objective Supply Portfolio under Disruption Risks -- 9.7 Bi-Objective Supply Portfolio under Disruption Risks -- 9.8 Computational Examples -- 9.9 Comments -- Exercises -- 10. Selection of a Dynamic Supply Portfolio in Supply Chains with Risks -- 10.1 Introduction -- 10.2 Multiperiod Supplier Selection and Order Allocation -- 10.3 Selection of a Dynamic Supply Portfolio to Minimize Expected Costs -- 10.4 Selection of a Dynamic Supply Portfolio to Minimize Expected Worst-Case Costs -- 10.5 Supply Portfolio for Best-Case and Worst-Case TDN Supplies -- 10.6 Computational Examples -- 10.7 Comments -- Exercises -- Part Three Coordinated Scheduling in Supply Chains -- 11. Hierarchical Integration of Medium-and Short-Term Scheduling -- 11.1 Introduction -- 11.2 Problem Description -- 11.3 Medium-Term Production Scheduling.

11.4 Short-Term Machine Assignment and Scheduling -- 11.5 Computational Examples -- 11.6 Comments -- Exercises -- 12. Coordinated Scheduling in Supply Chains with a Single Supplier -- 12.1 Introduction -- 12.2 Problem Description -- 12.3 Supply Chain Inventory -- 12.4 Coordinated Supply Chain Scheduling: An Integrated Approach -- 12.5 Coordinated Supply Chain Scheduling: A Hierarchical Approach -- 12.6 Computational Examples -- 12.7 Comments -- Exercises -- 13. Coordinated Scheduling in Supply Chains with Assignment of Orders to Suppliers -- 13.1 Introduction -- 13.2 Problem Description -- 13.3 Conditions for Feasibility of Customer Due Dates -- 13.4 Coordinated Supply Chain Scheduling: An Integrated Approach -- 13.5 Selected Multi-Objective Solution Approaches -- 13.6 Coordinated Supply Chain Scheduling: A Hierarchical Approach -- 13.7 Computational Examples -- 13.8 Comments -- Exercises -- 14. Coordinated Scheduling in Supply Chains without Assignment of Orders to Suppliers -- 14.1 Introduction -- 14.2 Problem Description -- 14.3 Coordinated Supply Chain Scheduling: An Integrated Approach -- 14.4 Selected Bi-Objective Solution Approaches -- 14.5 Coordinated Supply Chain Scheduling: A Hierarchical Approach -- 14.6 Computational Examples -- 14.7 Comments -- Exercises -- References -- Index.
Abstract:
A unified, systematic approach to applying mixed integer programming solutions to integrated scheduling in customer-driven supply chains Supply chain management is a rapidly developing field, and the recent improvements in modeling, preprocessing, solution algorithms, and mixed integer programming (MIP) software have made it possible to solve large-scale MIP models of scheduling problems, especially integrated scheduling in supply chains. Featuring a unified and systematic presentation, Scheduling in Supply Chains Using Mixed Integer Programming provides state-of-the-art MIP modeling and solutions approaches, equipping readers with the knowledge and tools to model and solve real-world supply chain scheduling problems in make-to-order manufacturing. Drawing upon the author's own research, the book explores MIP approaches and examples-which are modeled on actual supply chain scheduling problems in high-tech industries-in three comprehensive sections: Short-Term Scheduling in Supply Chains presents various MIP models and provides heuristic algorithms for scheduling flexible flow shops and surface mount technology lines, balancing and scheduling of Flexible Assembly Lines, and loading and scheduling of Flexible Assembly Systems Medium-Term Scheduling in Supply Chains outlines MIP models and MIP-based heuristic algorithms for supplier selection and order allocation, customer order acceptance and due date setting, material supply scheduling, and medium-term scheduling and rescheduling of customer orders in a make-to-order discrete manufacturing environment Coordinated Scheduling in Supply Chains explores coordinated scheduling of manufacturing and supply of parts as well as the assembly of products in supply chains with a single producer and single or multiple suppliers; MIP models for a single- or multiple-objective decision making are also

provided Two main decision-making approaches are discussed and compared throughout. The integrated (simultaneous) approach, in which all required decisions are made simultaneously using complex, monolithic MIP models; and the hierarchical (sequential) approach, in which the required decisions are made successively using hierarchies of simpler and smaller-sized MIP models. Throughout the book, the author provides insight on the presented modeling tools using AMPL® modeling language and CPLEX solver. Scheduling in Supply Chains Using Mixed Integer Programming is a comprehensive resource for practitioners and researchers working in supply chain planning, scheduling, and management. The book is also appropriate for graduate- and PhD-level courses on supply chains for students majoring in management science, industrial engineering, operations research, applied mathematics, and computer science.
Local Note:
Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2017. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries.
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