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Sinopsis
This book explains multi-objective optimization as an area of multicriteria decision making that deals with mathematical optimization problems involving more than one objective function that must be optimized simultaneously. Multi-objective optimization is used in many fields of science, including engineering, economics, and logistics, where there is a need to make optimal decisions in the presence of trade-offs between two or more conflicting objectives. Uncertain optimization refers to contexts where there is uncertainty in models and data. It potentially has various applications in different domains such as portfolio selection, inventory management, pollution reduction, sustainable development, resource allocation and reallocation, and performance analysis. The book encompasses various types of uncertainty in decision making namely fuzziness, possibility, Bayesian, stochastic, roughness, vagueness, and artificial intelligence and develops application areas in industrial cases. It includes 12 chapters presenting multiobjective decision models under one of the uncertainty types. In each chapter an implementation study is illustrated to show the applicability of the model.
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Acerca del autor
Hamed Fazlollahtabar earned a BSc and an MSc in industrial engineering from Mazandaran University of Science and Technology, Babol, Iran, in 2008 and 2010, respectively. He received his Ph.D. in Industrial and Systems Engineering from the Iran University of Science and Technology, Tehran, Iran, in 2015 and has completed a postdoctoral research fellowship at Sharif University of Technology, Tehran, Iran, in the area of reliability engineering for complex systems from October 2016 to March 2017. He joined the Department of Industrial Engineering at Damghan University, Damghan, Iran, in June 2017, and currently is working as an Associate Professor. He is a member of Iran Elites foundation. He has been chosen as Exemplary Researcher of Iran in all Engineering Diciplines, 2022 and Distinguished Young Industrial Engineering Researcher, Iran Academy of Science. 2023. He has been listed as world top 2% scientists in 2021, 2022, 2023 and 2024. His research interests are in uncertain decision making and analytics, industry 4.0+ production systems, reliability engineering, and sustainable supply chain planning.
De la contraportada
This book explains multi-objective optimization as an area of multicriteria decision making that deals with mathematical optimization problems involving more than one objective function that must be optimized simultaneously. Multi-objective optimization is used in many fields of science, including engineering, economics, and logistics, where there is a need to make optimal decisions in the presence of trade-offs between two or more conflicting objectives. Uncertain optimization refers to contexts where there is uncertainty in models and data. It potentially has various applications in different domains such as portfolio selection, inventory management, pollution reduction, sustainable development, resource allocation and reallocation, and performance analysis. The book encompasses various types of uncertainty in decision making namely fuzziness, possibility, Bayesian, stochastic, roughness, vagueness, and artificial intelligence and develops application areas in industrial cases. It includes 12 chapters presenting multiobjective decision models under one of the uncertainty types. In each chapter an implementation study is illustrated to show the applicability of he model.
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Uncertain Multi-objective Decision Making: Methods and Industrial Models (eng)
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Uncertain Multi-objective Decision Making: Methods and Industrial Models
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Springer, Springer Jan 2026, 2026
ISBN 10: 9819560349
ISBN 13: 9789819560349
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book explains multi-objective optimization as an area of multicriteria decision making that deals with mathematical optimization problems involving more than one objective function that must be optimized simultaneously. Multi-objective optimization is used in many fields of science, including engineering, economics, and logistics, where there is a need to make optimal decisions in the presence of trade-offs between two or more conflicting objectives. Uncertain optimization refers to contexts where there is uncertainty in models and data. It potentially has various applications in different domains such as portfolio selection, inventory management, pollution reduction, sustainable development, resource allocation and reallocation, and performance analysis. The book encompasses various types of uncertainty in decision making namely fuzziness, possibility, Bayesian, stochastic, roughness, vagueness, and artificial intelligence and develops application areas in industrial cases. It includes 12 chapters presenting multiobjective decision models under one of the uncertainty types. In each chapter an implementation study is illustrated to show the applicability of the model. 340 pp. Englisch. Nº de ref. del artículo: 9789819560349
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Uncertain Multi-objective Decision Making: Methods and Industrial Models
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Springer Nature Singapore, 2026
ISBN 10: 9819560349
ISBN 13: 9789819560349
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book explains multi-objective optimization as an area of multicriteria decision making that deals with mathematical optimization problems involving more than one objective function that must be optimized simultaneously. Multi-objective optimization is used in many fields of science, including engineering, economics, and logistics, where there is a need to make optimal decisions in the presence of trade-offs between two or more conflicting objectives. Uncertain optimization refers to contexts where there is uncertainty in models and data. It potentially has various applications in different domains such as portfolio selection, inventory management, pollution reduction, sustainable development, resource allocation and reallocation, and performance analysis. The book encompasses various types of uncertainty in decision making namely fuzziness, possibility, Bayesian, stochastic, roughness, vagueness, and artificial intelligence and develops application areas in industrial cases. It includes 12 chapters presenting multiobjective decision models under one of the uncertainty types. In each chapter an implementation study is illustrated to show the applicability of the model. Nº de ref. del artículo: 9789819560349
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Uncertain Multi-objective Decision Making: Methods and Industrial Models
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Springer, Springer Jan 2026, 2026
ISBN 10: 9819560349
ISBN 13: 9789819560349
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Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book explains multi-objective optimization as an area of multicriteria decision making that deals with mathematical optimization problems involving more than one objective function that must be optimized simultaneously. Multi-objective optimization is used in many fields of science, including engineering, economics, and logistics, where there is a need to make optimal decisions in the presence of trade-offs between two or more conflicting objectives. Uncertain optimization refers to contexts where there is uncertainty in models and data. It potentially has various applications in different domains such as portfolio selection, inventory management, pollution reduction, sustainable development, resource allocation and reallocation, and performance analysis. The book encompasses various types of uncertainty in decision making namely fuzziness, possibility, Bayesian, stochastic, roughness, vagueness, and artificial intelligence and develops application areas in industrial cases. It includes 12 chapters presenting multiobjective decision models under one of the uncertainty types. In each chapter an implementation study is illustrated to show the applicability of the model.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 340 pp. Englisch. Nº de ref. del artículo: 9789819560349
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