Computational Stochastic Programming: Models, Algorithms, and Implementation

This book is about stochastic programming (SP), a field of optimization that deals with mathematical programming problems involving uncertainty. SP problems are generally difficult to solve and the field has continued to evolve with contributions from various disciplines such as operations research, mathematics, and probability and statistics. SP has a wide range of application areas that include manufacturing, transportation, telecommunications, electricity power generation, health care, agriculture, forestry and wildfire management, mineral, oil and gas exploration, and finance. The purpose of this book is to provide a foundational and thorough treatment of the subject with a focus on models and algorithms and their computer implementation. Therefore, this book is suitable for readers with fundamental knowledge of linear programming, elementary analysis, probability and statistics, and some computer programming background. Specifically, computer programming knowledge is needed for model and algorithm implementation (coding) using available optimization software.