Hybrid slime mould algorithm with adaptive guided differential evolution algorithm for combinatorial and global optimization problems

•SMA-AGDE method is proposed for solving various optimization problems.•The algorithm performance is verified on CEC’17 benchmark.•The method performance is verified on 3 engineering and 2 combinatorial problems.•Efficiency of the proposed method is compared with many metaheuristics. The Slime Mould...

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Veröffentlicht in:	Expert systems with applications Jg. 174; S. 114689
Hauptverfasser:	Houssein, Essam H., Mahdy, Mohamed A., Blondin, Maude J., Shebl, Doaa, Mohamed, Waleed M.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Elsevier Ltd 15.07.2021 Elsevier BV
Schlagworte:	Adaptive algorithms Adaptive guided differential evolution algorithm (AGDE) Algorithms Combinatorial analysis Combinatorial optimization problems Compression springs Compression tests Covariance matrix Design engineering Design optimization Engineering design problems Evolutionary algorithms Evolutionary computation Exploration and exploitation Global optimization Global optimization problems Heuristic methods Machine learning Metaheuristics Mutation Optimization Performance evaluation Pressure vessels Roller bearings Search algorithms Slime Slime mould algorithm (SMA) Exploration and exploitation Combinatorial optimization problems Global optimization problems Engineering design problems Metaheuristics Slime mould algorithm (SMA) Adaptive guided differential evolution algorithm (AGDE)
ISSN:	0957-4174, 1873-6793
Online-Zugang:	Volltext
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