Название: Multi-Objective Optimization in Theory and Practice II : Metaheuristic Algorithms Автор: Andre A. Keller
Издательство: Bentham Science Publishers
Год: 2019
Страниц: 310
Язык: английский
Формат: pdf (true)
Размер: 53.2 MB
Multi-Objective Optimization in Theory and Practice is a simplified two-part approach to multi-objective optimization (MOO) problems. This second part focuses on the use of metaheuristic algorithms in more challenging practical cases. The book includes ten chapters that cover several advanced MOO techniques. These include the determination of Pareto-optimal sets of solutions, metaheuristic algorithms, genetic search algorithms and evolution strategies, decomposition algorithms, hybridization of different metaheuristics, and many-objective (more than three objectives) optimization and parallel computation.
The final section of the book presents information about the design and types of fifty test problems for which the Pareto-optimal front is approximated. For each of them, the package NSGA-II is used to approximate the Pareto-optimal front. It is an essential handbook for students and teachers involved in advanced optimization courses in engineering, information science and mathematics degree programs.
This book is typically user-oriented with theoretical and practical aspects. This book includes detailed examples, figures, test functions, and small-size applications from the literature. This book uses the commercial package Mathematica 7, and free software packages, including notably SciLab 5.5.2 (an alternative to MatLab), GENOCOP III, NSGA-II and a pseudo NSGA-III.
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