ASCA-PSO: Adaptive sine cosine optimization algorithm integrated with particle swarm for pairwise local sequence alignment

•Sine cosine algorithm is enhanced by hybridizing particle swarm optimization.•The hybridization is based on low level co-evolutionary hybrid scheme.•The proposed scheme produced better performance on mathematical benchmark functions.•Finding longest consecutive substring problem was used as testing...

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Veröffentlicht in:	Expert systems with applications Jg. 99; S. 56 - 70
Hauptverfasser:	Issa, Mohamed, Hassanien, Aboul Ella, Oliva, Diego, Helmi, Ahmed, Ziedan, Ibrahim, Alzohairy, Ahmed
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Elsevier Ltd 01.06.2018 Elsevier BV
Schlagworte:	Adaptive algorithms Algorithms Alignment Biological effects Computing time Heuristic Heuristic methods Longest consecutive substrings Meta-heuristics algorithms Operators Pairwise local alignment Parameters Particle swarm optimization Particle swarm optimization (PSO) Route optimization Sine cosine algorithm (SCA) Smith-Waterman alignment algorithm Trigonometric functions Sine cosine algorithm (SCA) Particle swarm optimization (PSO) Smith-Waterman alignment algorithm Longest consecutive substrings Meta-heuristics algorithms Pairwise local alignment
ISSN:	0957-4174, 1873-6793
Online-Zugang:	Volltext
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