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Supply Chain Disruption Management - Using Stochastic Mixed Integer Programming (Hardcover, 2nd ed. 2020)
Loot Price: R4,003
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Supply Chain Disruption Management - Using Stochastic Mixed Integer Programming (Hardcover, 2nd ed. 2020)
Series: International Series in Operations Research & Management Science, 291
Expected to ship within 12 - 19 working days
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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 riskneutral, risk-averse and
mean-risk decision-making in the presence of supply chain
disruption risks. The book focuses on integrated disruption
mitigation and recovery decision-making and innovative,
computationally efficient multi-portfolio approach 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 realworld supply chain disruption management problems,
illustrate the material presented and provide managerial insights.
Many propositions formulated in the book lead to a deep
understanding of the properties of developed stochastic mixed
integer programs and optimal solutions. 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 six
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 production and inventory scheduling, Part V deals
with selection of resilient supply portfolio in multitier supply
chain networks; and Part VI addresses selection of cybersecurity
safequards portfolio for disruption management of information flows
in supply chains.
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