UID:
almahu_9948130036002882
Format:
XI, 58 p. 26 illus., 25 illus. in color.
,
online resource.
Edition:
1st ed. 2020.
ISBN:
9783030248352
Series Statement:
SpringerBriefs in Computational Intelligence,
Content:
This book focuses on the most well-regarded and recent nature-inspired algorithms capable of solving optimization problems with multiple objectives. Firstly, it provides preliminaries and essential definitions in multi-objective problems and different paradigms to solve them. It then presents an in-depth explanations of the theory, literature review, and applications of several widely-used algorithms, such as Multi-objective Particle Swarm Optimizer, Multi-Objective Genetic Algorithm and Multi-objective GreyWolf Optimizer Due to the simplicity of the techniques and flexibility, readers from any field of study can employ them for solving multi-objective optimization problem. The book provides the source codes for all the proposed algorithms on a dedicated webpage.
In:
Springer eBooks
Additional Edition:
Printed edition: ISBN 9783030248345
Additional Edition:
Printed edition: ISBN 9783030248369
Language:
English
DOI:
10.1007/978-3-030-24835-2
URL:
https://doi.org/10.1007/978-3-030-24835-2
URL:
Volltext
(URL des Erstveröffentlichers)
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