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Methods of Nonsmooth Optimization in Stochastic Programming: From Conceptual Algorithms to Real-World Applications

Methods of Nonsmooth Optimization in Stochastic Programming: From Conceptual Algorithms to Real-World Applications

Hardcover

Series: International Operations Research & Management Science, Book 363

Business GeneralManagementGeneral Mathematics

ISBN10: 3031848365
ISBN13: 9783031848360
Publisher: Springer
Published: May 6 2025
Pages: 570
Weight: 2.19
Height: 1.25 Width: 6.14 Depth: 9.21
Language: English

This book presents a comprehensive series of methods in nonsmooth optimization, with a particular focus on their application in stochastic programming and dedicated algorithms for decision-making under uncertainty. Each method is accompanied by rigorous mathematical analysis, ensuring a deep understanding of the underlying principles. The theoretical discussions included are essential for comprehending the mechanics of various algorithms and the nature of the solutions they provide-whether they are global, local, stationary, or critical. The book begins by introducing fundamental tools from set-valued analysis, optimization, and probability theory. It then transitions from deterministic to stochastic optimization, starting with a thorough discussion of modeling, understanding uncertainty, and incorporating it into optimization problems. Following this foundation, the book explores numerical algorithms for nonsmooth optimization, covering well-known decomposition techniques and algorithms for convex optimization, mixed-integer convex programming, and nonconvex optimization. Additionally, it introduces numerical algorithms specifically for stochastic programming, focusing on stochastic programming with recourse, chance-constrained optimization, and detailed algorithms for both risk-neutral and risk-averse multistage stochastic programs.

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Van Ackooij, Wim Stefanus

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Business General