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|a Sawik, Tadeusz.
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|a Supply chain disruption management :
|b using stochastic mixed integer programming /
|c Tadeusz Sawik.
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|a 2nd ed.
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|a Cham :
|b Springer,
|c 2020.
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|a 1 online resource (487 pages)
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|a International Series in Operations Research and Management Science ;
|v 291
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| 504 |
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|a Includes bibliographical references and index.
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|a Print version record.
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|a Chapter 1 Introduction -- Part I Selection of Supply Portfolio -- Chapter 2. Selection of Static Supply Portfolio -- Chapter 3 Selection of Dynamic Supply Portfolio -- Chapter 4 Selection of Resilient Supply Portfolio -- Part II Integrated Selection of Supply Portfolio and Scheduling -- Chapter 5 Integrated Selection of Supply Portfolio and Scheduling of Production -- Chapter 6 Integrated Selection of Supply Portfolio and Scheduling of Production and Distribution -- Part III Equitably Efficient Selection of Supply Portfolio and Scheduling -- Chapter 7 A Fair Decision-Making under Disruption Risks -- Chapter 8 A Robust Decision-Making under Disruption Risks -- Part IV Selection of Primary and Recovery Portfolios and Scheduling -- Chapter 9 Selection of Primary and Recovery Supply Portfolio and Scheduling -- Chapter 10 Selection of Primary and Recovery Supply and Demand Portfolios and Scheduling -- Chapter 11 Selection of Primary and Recovery Supply and Demand Portfolios and Scheduling: A Two-Period Approach -- Chapter 12 Selection of Supply and Demand Portfolios and Production and Inventory Scheduling -- Part V Selection of Supply Portfolio in Multi-Tier Supply Chain Networks -- Chapter 13 Selection of Resilient Multi-Tier Supply Portfolio -- Chapter 14 Selection of Resilient Multi-Tier Supply Portfolio: A Two-Period Approach -- Part VI Information Flow Disruption Management -- Chapter 15 Selection of Cybersecurity Safequards Portfolio -- Index.
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|a This book deals with stochastic combinatorial optimization problems in supply chain disruption management, with a particular focus on management of disrupted flows in customer-driven supply chains. The problems are modeled using a scenario based stochastic mixed integer programming to address riskneutral, risk-averse and mean-risk decision-making in the presence of supply chain disruption risks. The book focuses on integrated disruption mitigation and recovery decision-making and innovative, computationally efficient multi-portfolio approach to supply chain disruption management, e.g., selection of primary and recovery supply portfolios, demand portfolios, capacity portfolios, etc. Numerous computational examples throughout the book, modeled in part on realworld supply chain disruption management problems, illustrate the material presented and provide managerial insights. Many propositions formulated in the book lead to a deep understanding of the properties of developed stochastic mixed integer programs and optimal solutions. In the computational examples, the proposed mathematical programming models are solved using an advanced algebraic modeling language such as AMPL and CPLEX, GUROBI and XPRESS solvers. The knowledge and tools provided in the book allow the reader to model and solve supply chain disruption management problems using commercially available software for mixed integer programming. Using the end-of chapter problems and exercises, the monograph can also be used as a textbook for an advanced course in supply chain risk management. After an introductory chapter, the book is then divided into six main parts. Part I addresses selection of a supply portfolio; Part II considers integrated selection of supply portfolio and scheduling; Part III looks at integrated, equitably efficient selection of supply portfolio and scheduling; Part IV examines integrated selection of primary and recovery supply and demand portfolios and production and inventory scheduling, Part V deals with selection of supply portfolio in multitier supply chain networks; and Part VI addresses selection of cybersecurity safequards portfolio for disruption management of information flows in supply chains.
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|a Business logistics
|x Management.
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|a Business logistics
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|a Decision making
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|a Industrial engineering
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|a Operations research
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|a Production engineering
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|i Print version:
|a Sawik, Tadeusz.
|t Supply Chain Disruption Management : Using Stochastic Mixed Integer Programming.
|d Cham : Springer, ©2020
|z 9783030448134
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| 830 |
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|a International series in operations research & management science ;
|v 291.
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| 856 |
4 |
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|u https://holycross.idm.oclc.org/login?auth=cas&url=https://link.springer.com/10.1007/978-3-030-44814-1
|y Click for online access
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