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Modified multiple search cooperative foraging strategy for improved artificial bee colony optimization with robustness analysis

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Abstract

Considering that extending the concept of bees partitioning into subgroups of foragers to the onlooker phase of the cooperative learning artificial bee colony (CLABC) strategy is not only feasible from algorithmic viewpoint but might reflect real behavioral foraging characteristics of bee swarms, this paper studies whether the performance of CLABC can be enhanced by developing a new model for the proposed cooperative foraging scheme. Relying on this idea, we design a modified cooperative learning artificial bee colony algorithm, referred to as mCLABC. The design procedure is built upon the definition of a partitioning scheme of onlookers allowing the generation of subgroups of foragers that might evolve differently by using specific solution search rules. In order to improve the involving of local and global search at both employed and onlooker levels, the multiple search mechanism is further tuned and scheduled according to a random selection strategy defined on the evolving parameters. Moreover, a detailed performance and robustness study of the proposed algorithm dealing with the analysis of the impact of different structural and parametric settings is conducted on benchmark optimization problems. Superior convergence performance, better solution quality, and strong robustness are the main features of the proposed strategy in comparison with recent ABC variants and advanced methods.

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Authors and Affiliations

  1. Applied Automation Laboratory, University of Boumerdès, 35000, Boumerdès, Algeria

    F. Harfouchi & H. Habbi

  2. Computer Engineering Department, Engineering Faculty, Erciyes University, 38039, Kayseri, Turkey

    C. Ozturk & D. Karaboga

Authors
  1. F. Harfouchi
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  2. H. Habbi
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  3. C. Ozturk
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  4. D. Karaboga
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Correspondence to H. Habbi.

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Mrs F. Harfouchi declares that she has no conflict of interest. Prof. H. Habbi declares that he has no conflict of interest. Dr. C. Ozturk declares that he has no conflict of interest. Prof. D. Karaboga declares that he has no conflict of interest.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Communicated by V. Loia.

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Harfouchi, F., Habbi, H., Ozturk, C. et al. Modified multiple search cooperative foraging strategy for improved artificial bee colony optimization with robustness analysis. Soft Comput 22, 6371–6394 (2018). https://doi.org/10.1007/s00500-017-2689-1

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