000			02091nam a22002057a 4500
005			20250115194305.0
008			250115b |||||||| |||| 00| 0 eng d
020			_a9783031579264
082			_a658.7 _bSAW
100			_aSawik, Tadeusz _99311
245			_aStochastic programming in supply chain risk management: _bresilience, viability, and cybersecurity
260			_bSpringer _aCham _c2024
300			_axxix, 350 p.
365			_aEUR _b149.99
490			_aInternational Series in Operations Research and Management Science
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 (https://link.springer.com/book/10.1007/978-3-031-57927-1)
650			_aSupply chain resilience _920723
650			_aSupply chain risk management _96004
942			_cBK _2ddc
999			_c8555 _d8555