Robustness Analysis in Decision Aiding, Optimization, and Analytics

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This book explores recent advances in robustness analysis within decision aiding, optimization, and analytics. It illustrates the challenges robustness presents in various operations research and management science (OR/MS) contexts, alongside methodologies proposed from diverse perspectives. In addition to methodological developments, it showcases applications of robust techniques in engineering and management, highlighting real-world robustness issues and their solutions through OR/MS advancements. Robustness analysis aims to promote solutions acceptable under a wide range of hypotheses, assumptions, and estimates. Traditionally, robustness in OR/MS has focused on optimization under uncertainty, but scholars have expanded this view to encompass the broader decision support nature of OR/MS methodologies. As new challenges arise in the "big data" era, characterized by rapid information flow and complexity, the relevance of robustness issues increases. These challenges underscore the importance of providing sound decision support through advanced analytic tools, making the insights presented in this volume particularly timely and essential for strategic and operational decision-making on a global scale.