Supply Chain Disruption Management Using Stochastic Mixed Integer Programming / Tadeusa Sawik.
Sawik, Tadeusz, author.
2018
HD38.5 .S29 2018
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Title
Supply Chain Disruption Management Using Stochastic Mixed Integer Programming / Tadeusa Sawik.
Author
Sawik, Tadeusz, author.
ISBN
9783319588230 (electronic book)
3319588230 (electronic book)
9783319588223
3319588222
DOI
https://doi.org/10.1007/978-3-319-58823-0
Published
Cham, Switzerland : Springer, 2018.
Language
English
Description
1 online resource.
Item Number
10.1007/978-3-319-58823-0 doi
Call Number
HD38.5 .S29 2018
Dewey Decimal Classification
658.5/00285
Summary
"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 risk-neutral, risk-averse and mean-risk decision-making in the presence of supply chain disruption risks. The book focuses on innovative, computationally efficient portfolio approaches 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 real-world supply chain disruption management problems, illustrate the material presented and provide managerial insights. 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 five 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 scheduling; and Part V addresses disruption management of information flows in supply chains."-- Provided by publisher.
Bibliography, etc. Note
Includes bibliographical references and index.
Access Note
Access limited to authorized users.
Digital File Characteristics
text file PDF
Source of Description
Description based on online resource; title from digital title page (viewed on August 04, 2017).
Series
International series in operations research & management science ; 256.
Available in Other Form
Print version: 3319588222
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Preface; Scope; Content; Audience; Acknowledgements; Contents; Acronyms; List of Figures; List of Tables; 1 Introduction; 1.1 Overview of Supply Chain Disruption Management; 1.2 Value-at-Risk Versus Conditional Value-at-Risk; 1.3 Local, Regional and Global Disruptions; 1.4 Two-level Versus Multi-level Disruptions; 1.5 Risk-Neutral, Risk-Averse and Mean-Risk Decision-Making; Part I Selection of Supply Portfolio; 2 Selection of Static Supply Portfolio; 2.1 Introduction; 2.2 Problem Description; 2.3 Models for Risk-Neutral Decision-Making; 2.4 Models for Risk-Averse Decision-Making

2.5 Models for Mean-Risk Decision-Making2.6 Computational Examples; 2.6.1 Single-Region Sourcing; 2.6.2 Multi-region Sourcing; 2.7 Notes; 3 Selection of Dynamic Supply Portfolio; 3.1 Introduction; 3.2 Problem Description; 3.3 Models for Risk-Neutral Decision-Making; 3.3.1 Dynamic Supply Portfolio for All-or-Nothing Delivery Scenarios; 3.4 Models for Risk-Averse Decision-Making; 3.5 Models for Mean-Risk Decision-Making; 3.6 Computational Examples; 3.6.1 Worst-case Scenarios with Longest Delays and Disruptions ; 3.7 Notes; 4 Selection of Resilient Supply Portfolio; 4.1 Introduction

4.2 Problem Description: Single-Level Protection 4.3 Resilient Supply Portfolio with Single-Level Protection; 4.3.1 Model for Risk-Neutral Decision-Making; 4.3.2 Model for Risk-Averse Decision-Making; 4.3.3 Model for Mean-Risk Decision-Making; 4.4 Protection Index; 4.5 Resilient Supply Portfolio with Multi-Level Protection; 4.6 Computational Examples; 4.6.1 Single-Level Protection; 4.6.2 Multi-level Protection; 4.7 Notes; Part II Integrated Selection of Supply Portfolio and Scheduling; 5 Integrated Selection of Supply Portfolio and Scheduling of Production; 5.1 Introduction

5.2 ProbleDescription 5n5.3 Models for Risk-Neutral Decision-Making; 5.3.1 Minimization of Cost; 5.3.2 Maximization of Customer Service Level; 5.4 Models for Risk-Averse Decision-Making; 5.4.1 Minimization of Cost; 5.4.2 Maximization of Customer Service Level; 5.5 Model for Mixed Mean-Risk Decision-Making; 5.6 Computational Examples; 5.6.1 Single Versus Dual Sourcing; 5.6.2 Single Versus Multiple Sourcing; 5.6.3 Order Versus Demand Fulfillment Rate; 5.6.4 Conditional Service-At Risk Versus Expected Cost; 5.7 Notes

6 Integrated Selection of Supply Portfolio and Scheduling of Production and Distribution 6.1 Introduction; 6.2 Problem Description; 6.3 Models for Risk-Neutral Decision-Making; 6.3.1 Scheduling with Single Batch Shipping; 6.3.2 Scheduling with Individual and Immediate Shipping; 6.3.3 Scheduling with Multiple Batch Shipping and Limited Transportation Capacity; 6.4 Models for Risk-Averse Decision-Making; 6.5 Expected Value Problem; 6.6 Computational Examples; 6.6.1 Risk-Neutral Decision-Making; 6.6.2 Risk-Averse Decision-Making; 6.6.3 Expected Value
Based Decision-Making; 6.7 Notes.

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