Improved prairie dog optimization algorithm by dwarf mongoose optimization algorithm for optimization problems

Recently, optimization problems have been revised in many domains, and they need powerful search methods to address them. In this paper, a novel hybrid optimization algorithm is proposed to solve various benchmark functions, which is called IPDOA. The proposed method is based on enhancing the search...

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Veröffentlicht in:	Multimedia tools and applications Jg. 83; H. 11; S. 32613 - 32653
Hauptverfasser:	Abualigah, Laith, Oliva, Diego, Jia, Heming, Gul, Faiza, Khodadadi, Nima, Hussien, Abdelazim G, Shinwan, Mohammad Al, Ezugwu, Absalom E., Abuhaija, Belal, Zitar, Raed Abu
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.03.2024 Springer Nature B.V Springer Verlag
Schlagworte:	Algorithms Benchmarks Computer Communication Networks Computer Science Convergence Data Structures and Information Theory Evolution Mathematical functions Methods Multimedia Multimedia Information Systems Optimization Optimization algorithms Optimization techniques Parameter identification Physics Prairie dogs Search methods Search process Snakes Special Purpose and Application-Based Systems Benchmark functions Prairie dog optimization algorithm Optimization problems Dwarf mongoose optimization algorithm Meta-heuristics
ISSN:	1573-7721, 1380-7501, 1573-7721
Online-Zugang:	Volltext
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