Druck auf Anfrage Neuware - Printed after ordering - This book provides a broad coverage of the recent advances in robustness analysis in decision aiding, optimization, and analytics. It offers a comprehensive illustration of the challenges that robustness raises in different operations research and management science (OR/MS) contexts and the methodologies proposed from multiple perspectives. Aside from covering recent methodological developments, this volume also features applications of robust techniques in engineering and management, thus illustrating the robustness issues raised in real-world problems and their resolution within advances in OR/MS methodologies.Robustness analysis seeks to address issues by promoting solutions, which are acceptable under a wide set of hypotheses, assumptions and estimates. In OR/MS, robustness has been mostly viewed in the context of optimization under uncertainty. Several scholars, however, have emphasized the multiple facets of robustness analysis in a broader OR/MS perspective that goes beyond the traditional framework, seeking to cover the decision support nature of OR/MS methodologies as well. As new challenges emerge in a 'big-data'' era, where the information volume, speed of flow, and complexity increase rapidly, and analytics play a fundamental role for strategic and operational decision-making at a global level, robustness issues such as the ones covered in this book become more relevant than ever for providing sound decision support through more powerful analytic tools.

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Detalles bibliogr�ficos

T�tulo: Robustness Analysis in Decision Aiding, Optimization, and Analytics
Editor: Birkh�user
Fecha de publicaci�n: 2018
Idioma: Ingl�s
ISBN 10: 331981432X
ISBN 13: 9783319814322
Encuadernaci�n: Taschenbuch
Estado: Neu
Dimensiones: 235�mil�metros de ancho por 155 de alto por 19 de largo
Peso: 522 gramos

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Sinopsis

This book provides a broad coverage of the recent advances in robustness analysis in decision aiding, optimization, and analytics. It offers a comprehensive illustration of the challenges that robustness raises in different operations research and management science (OR/MS) contexts and the methodologies proposed from multiple perspectives. Aside from covering recent methodological developments, this volume also features applications of robust techniques in engineering and management, thus illustrating the robustness issues raised in real-world problems and their resolution within advances in OR/MS methodologies.

Robustness analysis seeks to address issues by promoting solutions, which are acceptable under a wide set of hypotheses, assumptions and estimates. In OR/MS, robustness has been mostly viewed in the context of optimization under uncertainty. Several scholars, however, have emphasized the multiple facets of robustness analysis in a broader OR/MS perspective that goes beyond the traditional framework, seeking to cover the decision support nature of OR/MS methodologies as well. As new challenges emerge in a "big-data'" era, where the information volume, speed of flow, and complexity increase rapidly, and analytics play a fundamental role for strategic and operational decision-making at a global level, robustness issues such as the ones covered in this book become more relevant than ever for providing sound decision support through more powerful analytic tools.

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Michael Doumpos is associate professor of operations research at the School of Production Engineering and Management of the Technical University of Crete, Greece. His research interests include multiple criteria decision making, decision support systems, business intelligence, and financial risk management. He has published over 70 research papers in premier journals in operations research, management science, and finance. He has also authored and edited several books on intelligent decision support, multicriteria analysis, and financial decision making, and he has guest-edited more than 10 special issues on these areas for leading international journals. He serves as managing editor of the International Journal of Multicriteria Decision Making, and associate editor of Omega and the International Journal of Financial Engineering and Risk Management. He has been involved in a number of research projects funded by public organizations and the private sector, regarding the implementation of decision support systems and data analytic techniques in several areas such as finance, banking, energy management, and shipping.

Constantin Zopounidis is Professor of financial engineering and operations research at the Technical University of Crete (Greece), Distinguished Research Professor in Audencia Nantes School of Management (France), and Senior Academician of the Royal Academy of Economics and Financial Sciences of Spain, and member of the Royal Academy of Doctors of Spain. His research interests include financial engineering, financial risk management, and multiple criteria decision making. He has published over 300 papers in premier international journals, edited volumes, and conference proceedings. He has also published several books and edited volumes on financial engineering and operations research. Prof. Zopounidis is co-Editor-in-Chief of Operational Research-An International Journal (Springer), and editor-in-chief of the International Journalof Multicriteria Decision Making (Inderscience), and the International Journal of Financial Engineering and Risk Management (Inderscience). He also serves as topical editor for the Wiley Encyclopedia of Operations Research and Management Science, and associate editor and member of the editorial board for several journals such as the European Journal of Operational Research, the EURO Journal on Decision Processes, Optimization Letters, the International Transactions in Operational Research, among others. In recognition of his research work, he has received awards and honorary distinctions from several international research organizations. In 2013 he received the Edgeworth-Pareto Award from the International Society on Multiple Criteria Decision Making. Prof. Zopounidis is also the founder and elected president of the Financial Engineering and Banking Society.

Evangelos Grigoroudis is Associate Professor on management of quality processes in the School of Production Engineering and Management of the Technical University of Crete, Greece (2002-). He followed postgraduate studies in Technical University of Crete, Greece from where he received his Ph.D. degree in 1999. He has received distinctions from the Hellenic Operational Research Society, the Academy of Business and Administrative Sciences, the World Automation Congress, the Foundation of Ioannis and Vasileia Karayianni, the Technical University of Crete, and the State Scholarships Foundation of Greece. He acts as reviewer for more than 50 scientific journals, and he is associate editor of the Operational Research: An International Journal, International Journal of Decision Support Systems, Journal of Knowledge Economy, International Journal of Social Ecology and Sustainable Development, Journal of Innovation and Entrepreneurship, Journal of Technology, Innovation and Education, and International Journal of Food and Beverage Manufacturing and Business Models and member of the Editorial Boardof the scientific journals: International Journal of Information and Decision Sciences, International Journal of Information Systems in the Service Sector, International Journal of Multicriteria Decision Making. He is author/editor of 17 books on the measurement of service quality, the business strategy and management, and the multicriteria decision aid approaches, as well as of a significant number of research reports and papers in scientific journals and conference proceedings. He has participated in the organisation of many scientific conferences and he has numerous presentations in scientific conferences. His research interests include service quality measurement processes, customer and employee satisfaction, performance evaluation, business excellence, operational research (evaluation methodologies and techniques), multicriteria decision analysis, data analysis (qualitative data analysis methods), and marketing (market and customer satisfaction surveys).

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