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Multi-Objective Combinatorial Optimization Problems and Solution Methods

Language EnglishEnglish
Book Paperback
Book Multi-Objective Combinatorial Optimization Problems and Solution Methods Mehdi Toloo
Libristo code: 37023964
Publishers Elsevier Books, February 2022
Multi-Objective Combinatorial Optimization Problems and Solution Methods discusses the results of a... Full description
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Multi-Objective Combinatorial Optimization Problems and Solution Methods discusses the results of a recent multi-objective combinatorial optimization achievement that considered metaheuristic, mathematical programming, heuristic, hyper heuristic and hybrid approaches. In other words, the book presents various multi-objective combinatorial optimization issues that may benefit from different methods in theory and practice. Combinatorial optimization problems appear in a wide range of applications in operations research, engineering, biological sciences and computer science, hence many optimization approaches have been developed that link the discrete universe to the continuous universe through geometric, analytic and algebraic techniques. This book covers this important topic as computational optimization has become increasingly popular as design optimization and its applications in engineering and industry have become ever more important due to more stringent design requirements in modern engineering practice. Presents a collection of the most up-to-date research, providing a complete overview of multi-objective combinatorial optimization problems and applications Introduces new approaches to handle different engineering and science problems, providing the field with a collection of related research not already covered in the primary literature Demonstrates the efficiency and power of the various algorithms, problems and solutions, including numerous examples that illustrate concepts and algorithms

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About the book

Full name Multi-Objective Combinatorial Optimization Problems and Solution Methods
Language English
Binding Book - Paperback
Date of issue 2022
Number of pages 314
EAN 9780128237991
Libristo code 37023964
Publishers Elsevier Books
Weight 660
Dimensions 191 x 235
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