Metaheuristics for Finding Multiple Solutions

by Epitropakis, Michael G. Fieldsend, Jonathan E. Li, Xiaodong Preuß, Mike

Type Book

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Title Statements

Full title :Metaheuristics for Finding Multiple Solutions / edited by Mike Preuss, Michael G. Epitropakis, Xiaodong Li, Jonathan E. Fieldsend.

Summary

This book presents the latest trends and developments in multimodal optimization and niching techniques. Most existing optimization methods are designed for locating a single global solution. However, in real-world settings, many problems are "multimodal" by nature, i.e., multiple satisfactory solutions exist. It may be desirable to locate several such solutions before deciding which one to use. Multimodal optimization has been the subject of intense study in the field of population-based meta-heuristic algorithms, e.g., evolutionary algorithms (EAs), for the past few decades. These multimodal optimization techniques are commonly referred to as "niching" methods, because of the nature-inspired "niching" effect that is induced to the solution population targeting at multiple optima. Many niching methods have been developed in the EA community. Some classic examples include crowding, fitness sharing, clearing, derating, restricted tournament selection, speciation, etc. Nevertheless, applying these niching methods to real-world multimodal problems often encounters significant challenges. To facilitate the advance of niching methods in facing these challenges, this edited book highlights the latest developments in niching methods. The included chapters touch on algorithmic improvements and developments, representation, and visualization issues, as well as new research directions, such as preference incorporation in decision making and new application areas. This edited book is a first of this kind specifically on the topic of niching techniques. This book will serve as a valuable reference book both for researchers and practitioners. Although chapters are written in a mutually independent way, Chapter 1 will help novice readers get an overview of the field. It describes the development of the field and its current state and provides a comparative analysis of the IEEE CEC and ACM GECCO niching competitions of recent years, followed by a collection of open research questions and possible research directions that may be tackled in the future.

Edition Statements

Publication Date:2021.
Edition:1st ed. 2021

Publication Statements

Publisher(s):Imprint: Springer, Springer International Publishing
Place of Publication:Cham
Language:eng
Publication Date:2021.

The Physical Object

Description:1 online resource (XII, 315 p. 115 illus., 75 illus. in color. :) : online resource.

Edition Identifiers

ISBN:9783030795535, 3030795535
DOI:10.1007/978-3-030-79553-5.
oclc:on1301024916
LC Classification:TA347.A78
Dewey Decimal:006.3

Introduction -- Theoretical Studies and Analysis of Niching Methods -- Parameter Adaptation in Niching Methods -- Lowering Computational Cost -- Scalability -- Performance Metrics -- Comparative Studies -- Methods for Machine Learning and Clustering -- Real-World Applications.

Subjects

artificial intelligence Computational Intelligence Computer Science Electronic Data Processing Informatique Intelligence artificielle Intelligence informatique Mathematical optimization Operations research Operations Research and Decision Theory Optimisation mathématique Optimization Recherche opérationnelle Theory of Computation