Literature DB >> 33817020

An integrated cuckoo search optimizer for single and multi-objective optimization problems.

Xiangbo Qi1, Zhonghu Yuan1, Yan Song2.   

Abstract

Integrating heterogeneous biological-inspired strategies and mechanisms into one algorithm can avoid the shortcomings of single algorithm. This article proposes an integrated cuckoo search optimizer (ICSO) for single objective optimization problems, which incorporates the multiple strategies into the cuckoo search (CS) algorithm. The paper also considers the proposal of multi-objective versions of ICSO called MOICSO. The two algorithms presented in this paper are benchmarked by a set of benchmark functions. The comprehensive analysis of the experimental results based on the considered test problems and comparisons with other recent methods illustrate the effectiveness of the proposed integrated mechanism of different search strategies and demonstrate the performance superiority of the proposed algorithm.
© 2021 Qi et al.

Entities:  

Keywords:  Cuckoo search algorithm; Differential evolution; Integrated cuckoo search algorithm; Meta-heuristic

Year:  2021        PMID: 33817020      PMCID: PMC7959647          DOI: 10.7717/peerj-cs.370

Source DB:  PubMed          Journal:  PeerJ Comput Sci        ISSN: 2376-5992


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Authors:  S Kirkpatrick; C D Gelatt; M P Vecchi
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