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020 _a9783031579264
041 _aeng
082 _a658.5
_bSawS
100 _aSawik, Tadeusz
245 _aStochastic Programming in Supply Chain Risk Management :
_bResilience, Viability, and Cybersecurity /
_cTadeusz Sawik
260 _aSwitzerland:
_bSpringer International Publishing;
_c©2024
300 _axxix, 350p.
440 _aInternational Series in Operations Research & Management Science
_vv.359
520 _aThis book offers a novel multi-portfolio approach and stochastic programming formulations for modeling and solving contemporary supply chain risk management problems. The focus of the book is on supply chain resilience under propagated disruptions, supply chain viability under severe crises, and supply chain cybersecurity under direct and indirect cyber risks. The content is illustrated with numerous computational examples, some of which are modeled on real-world supply chains subject to severe multi-regional or global crises, such as pandemics. In the computational examples, the proposed stochastic programming models are solved using an advanced algebraic modeling language AMPL and GUROBI solver. The book seamlessly continues the journey begun in the author’s previously published book “Supply Chain Disruption Management: Using Stochastic Mixed Integer Programming.” It equips readers with the knowledge, tools, and managerial insights needed to effectively model and address modern supply chain risk management challenges. As such, the book is designed for practitioners and researchers who are interested in supply chain risk management. Master’s and Ph.D. students in disciplines like supply chain management, operations research, industrial engineering, applied mathematics, and computer science will also find the book a valuable resource.
650 _aSupply Chain Management
650 _aOperations Research/Decision Theory
650 _aProbability Theory and Stochastic Processes
650 _aRisk Management
650 _aSystems and Data Security
650 _aOptimization
942 _cBK
999 _c7800
_d7800