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Soft Computing
Erschienen in: Soft Computing 21/2019

24.04.2019 | Foundations

A hybrid many-objective cuckoo search algorithm

verfasst von: Zhihua Cui, Maoqing Zhang, Hui Wang, Xingjuan Cai, Wensheng Zhang

Erschienen in: Soft Computing | Ausgabe 21/2019

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Abstract

Cuckoo search (CS) is an excellent population-based algorithm and has shown promising performance in dealing with single- and multi-objective optimization problems. However, for many-objective optimization problems (MaOPs), CS cannot be directly employed. So far, few paper have been reported to use CS to solve MaOPs. In this paper, we try to propose a hybrid many-objective cuckoo search (HMaOCS) for MaOPs. In HMaOCS, the standard CS is firstly modified to effectively deal with MaOPs. Then, non-dominated sorting and the strategy of reference points are employed to ensure the convergence and diversity. In order to verify the performance of HMaOCS, DTLZ and WFG benchmark sets are utilized in the experiments. Experimental results show that HMaOCS can achieve promising performance compared with five other well-known many-objective optimization algorithms.
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Metadaten
Titel
A hybrid many-objective cuckoo search algorithm
verfasst von
Zhihua Cui
Maoqing Zhang
Hui Wang
Xingjuan Cai
Wensheng Zhang
Publikationsdatum
24.04.2019
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 21/2019
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-019-04004-4

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