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.

Autorentext
Tadeusz Sawik is a Professor of Industrial Engineering and Operations Research at AGH University of Science and Technology in Kraków, Poland. He has been Associate Dean for Research at School of Management, Chair of the Department of Computer Integrated Manufacturing and Chair of the Department of Operations Research and Information Technology. He received the MS degree in mechanical engineering, the PhD degree in control engineering and the ScD (habilitation) degree in operations research, all from AGH University. He has been a visiting professor in Germany, Japan, Sweden and Switzerland and he has served as a research advisor of Motorola for several years. Five times he received Scientific Excellence Award from the Minister of Science and Higher Education, one of the most prestigious award in Poland. He has published numerous books (including Production Planning and Scheduling in Flexible Assembly Systems, Springer, 1998 and Scheduling in Supply Chains Using Mixed Integer Programming, Wiley, 2011), and more than 150 individual articles in refereed journals. His current research interests are in the area of supply chain optimization, risk management, scheduling and integer programming. In the 50th volume anniversary issue of International Journal of Production Research (IJPR), a flagship journal in production research, he has been recognized as one of the top authors who have had the greatest impact on defining the knowledge represented in IJPR. He is the founding Editor-in-Chief of Decision Making in Manufacturing and Services (AGH University Press).

Inhalt
Chapter 1. Introduction.- Chapter 2. Selection of Static Supply Portfolio.- Chapter 3. Selection of Dynamic Supply Portfolio.- Chapter 4. Selection of Resilient Supply Portfolio.- Chapter 5. Integrated Selection of Supply Portfolio and Scheduling of Production.- Chapter 6. Integrated Selection of Supply Portfolio and Scheduling of Production and Distribution.- Chapter 7. A Fair Decision-Making under Disruption Risks.- Chapter 8. A Robust Decision-Making under Disruption Risks.- 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 Cybersecurity Safeguards Portfolio.