TY  - BOOK
AU  - Sawik,Tadeusz
ED  - SpringerLink (Online service)
TI  - Stochastic Programming in Supply Chain Risk Management: Resilience, Viability, and Cybersecurity 
T2  - International Series in Operations Research & Management Science,
SN  - 9783031579271
AV  - HD38.5 
PY  - 2024///
CY  - Cham
PB  - Springer Nature Switzerland, Imprint: Springer
KW  - Business logistics
KW  - Operations research
KW  - Stochastic models
KW  - Financial risk management
KW  - Data protection
KW  - Mathematical optimization
KW  - Supply Chain Management
KW  - Operations Research and Decision Theory
KW  - Stochastic Modelling
KW  - Risk Management
KW  - Data and Information Security
KW  - Optimization
N1  - Introduction -- Supply Chain Resilience: Supply Portfolio -- Supply Chain Resilience: Multi-Tier Supply Portfolio -- Supply Chain Resilience under Ripple Effect -- Supply Chain Viability: Risk-Neutral Decision-Making -- Supply Chain Viability: Risk-Averse Decision-Making -- Supply Chain Reshoring: Risk-Neutral vs Risk-Averse Decision-Making -- Supply Chain Cybersecurity: A Linear Optimization Model -- Supply Chain Cybersecurity: Direct and Indirect Cyber Risks -- Supply Chain Cybersecurity: Security Controls with Maximum Cybersecurity Value
N2  - This 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
UR  - https://doi.org/10.1007/978-3-031-57927-1
ER  -