Multicriteria and Optimization Models for Risk, Reliability, and Maintenance Decision Analysis

ISBN 10: 3030896498 / ISBN 13: 9783030896492

Editore: Springer International Publishing, 2023

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Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents advances in risk analysis, reliability and maintenance (RRM) and MCDMIntegrates fundamental concepts from both areas of RRM and decision makingIncludes multiobjective topics such as linear and nonlinear programmingAdiel Tei.

Codice articolo 884945372

Dati bibliografici

• Titolo: Multicriteria and Optimization Models for Risk, Reliability, and Maintenance Decision Analysis
• Editore: Springer International Publishing
• Data di pubblicazione: 2023
• Lingua: Inglese
• ISBN 10: 3030896498
• ISBN 13: 9783030896492
• Rilegatura: Brossura
• Condizione: New

Descrizione articolo

Riassunto

This book considers a broad range of areas from decision making methods applied in the contexts of Risk, Reliability and Maintenance (RRM). Intended primarily as an update of the 2015 book Multicriteria and Multiobjective Models for Risk, Reliability and Maintenance Decision Analysis, this edited work provides an integration of applied probability and decision making. Within applied probability, it primarily includes decision analysis and reliability theory, amongst other topics closely related to risk analysis and maintenance. 

In decision making, it includes multicriteria decision making/aiding (MCDM/A) methods and optimization models. Within MCDM, in addition to decision analysis, some of the topics related to mathematical programming areas are considered, such as multiobjective linear programming, multiobjective nonlinear programming, game theory and negotiations, and multiobjective optimization. Methods related to these topics have been applied to the context of RRM. In MCDA, several other methods are considered, such as outranking methods, rough sets and constructive approaches. 

The book addresses an innovative treatment of decision making in RRM, improving the integration of fundamental concepts from both areas of RRM and decision making. This is accomplished by presenting current research developments in decision making on RRM. Some pitfalls of decision models on practical applications on RRM are discussed and new approaches for overcoming those drawbacks are presented.

Informazioni sull?autore

Adiel Teixeira de Almeida is currently Full Professor of management engineering at Universidade Federal de Pernambuco, Brazil. He is on the Editorial Board of a number of journals, such as Group Decision and Negotiation, Information Sciences and IMA Journal of Management Mathematics. Professor de Almeida's interests are in decision-making related to multiple objectives and group decision problems, including methodological issues and applications.

Love Ekenberg is a Professor in Computer and Systems Sciences at Stockholm University, Kista, Sweden, and he is a Senior Research Scholar at the International Institute for Applied Systems Analysis (IIASA) in Austria. His research interests include risk and decision analysis, logic verification of complex industrial systems, and development cooperation.

Philip Scarf is a Professor of Management Mathematics at Cardiff Business School, Cardiff University, UK.  He is Co-Editor-in-Chief, IMA Journal of Management Mathematics.  His research interests include applying Statistics and Operations Research in reliability and maintenance, manufacturing informatics, autonomous systems, corrosion science, and sports.

Enrico Zio is Director of the Chair on Complex Systems and the Energy Challenge at Ecole Centrale Paris and Supelec, Fondation Europeenne pour l’Energie Nouvelle – EdF, France and is a Full Professor in the Energy Department at Politecnico di Milano, Italy. His research interests include the integration of nuclear plant engineering skills, signal security and analysis in the development and application of advanced computational methods and models for evaluating the safety of nuclear components and systems, as well as the operation and safety maintenance of nuclear components and systems. He is the author of five books on reliability and risk assessment.

Ming Zuo is a Professor of Mechanical Engineering at the University of Alberta in Edmonton, Canada. His research interests include Reliability Engineering, Vibration Monitoring, Fault Diagnosis, Signal Processing, Condition-Based Maintenance Optimization, and Manufacturing Systems.