Uncertain Multi-objective Decision Making: Methods and Industrial Models
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Beschreibung
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.
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.
Demonstrates innovative methods of multi-objective decision making Includes industrial cases for implementation studies Covers all types of uncertainty in multi-objective decision making
Autor*in
Hamed Fazlollahtabar
Themen in »Uncertain Multi-objective Decision Making: Methods and Industrial Models«
Multi objective optimization fuzzy probabilistic fuzzy PROMETHEE full fuzzy linear program Vagueness genetic algorithm (GA) possible vague robust ranking technique Multiple Objective Decision Making Rough Set Possibility theory Bayesian theory Stochastic parameters Ant colony optimization Particle Swarm Optimization (PSO)