Multi-objective grey wolf optimizer

Seyedali Mirjalili; Jin Song Dong

doi:10.1007/978-3-030-24835-2_5

Multi-objective grey wolf optimizer

Seyedali Mirjalili, Jin Song Dong

Artificial Intelligence Research and Optimization

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

4 Citations (Scopus)

Abstract

Metaheuristics have become very popular in the last two decades. This class of problem solving techniques includes a wide range of algorithms to find reasonably good solutions for problems where deterministic methods are not efficient. Their name come from their mechanism, in which they do not required problem-specific heuristic information. Such methods are stochastic and consider problems as a black box.

Original language	English
Title of host publication	SpringerBriefs in Applied Sciences and Technology
Publisher	Springer Verlag
Pages	47-58
Number of pages	12
DOIs	https://doi.org/10.1007/978-3-030-24835-2_5
Publication status	Published - 1 Jan 2020

Publication series

Name	SpringerBriefs in Applied Sciences and Technology
ISSN (Print)	2191-530X
ISSN (Electronic)	2191-5318

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10.1007/978-3-030-24835-2_5

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Multi-objective grey wolf optimizer

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