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This textbook provides researchers, post-graduate students, and practitioners with a systematic framework for coping with uncertainty when making facility location decisions. In …
This book presents recent findings and results concerning the solutions of especially finite state-space Markov decision problems and determining Nash equilibria for related …
This book is a rigorous but practical presentation of the techniques of uncertainty quantification, with applications in R and Python. This volume includes mathematical arguments …
This book explores recent developments and exciting challenges in operations research and mathematical optimization. It provides the following in a unified and carefully developed …
This book demonstrates how decision-making models can be applied to solve specific real-life problems, with a particular emphasis on wind energy. In a step-by-step manner, it …
This book is a rigorous but practical presentation of the Bayesian techniques of uncertainty quantification, with applications in R. This volume includes mathematical arguments at …
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 …
This book provides relevant theoretical frameworks and the latest empirical research findings in Operations Research (OR) and Management Science (MS) as applied to sustainability. …
The objective of ONLINE OPTIMIZATION is to provide a systematic survey of the methodology. From the methodological survey, the book then covers a variety of applications of online …
This book presents the state-of-the-art applications of machine learning in the finance domain with a focus on financial product modeling, which aims to advance the model …