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Erschienen in: Soft Computing 6/2018

27.05.2017 | Foundations

Variations of cohort intelligence

verfasst von: N. S. Patankar, Anand J. Kulkarni

Erschienen in: Soft Computing | Ausgabe 6/2018

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Abstract

A cohort refers to a group of candidates interacting and competing with one another. The basic idea of cohort is inspired from the social tendency of following/learning from one another and adapting the qualities of certain candidate. Based upon this approach, seven variations of cohort intelligence (CI) are presented in this paper. The seven variations of CI are: follow best, follow better, follow worst, follow itself, follow median, follow roulette wheel selection and alienate-and-random selection. The proposed variations are tested on seven multimodal and three uni-modal unconstrained test functions, and the numerical results are analyzed to decide which variation works best for a particular type of problem. The performance of these variations is compared with some well-known algorithms namely PSO, CMAES, ABC, JDE, CLPSO, SADE and BSA. The analysis of variations gives very important insight about the strategy that should be followed while working in a cohort. The variations proposed may provide insight into variegated applicability domain of the CI methodology. The choice of the right variation may also further open doors for CI to solve different real-world problems.

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Metadaten
Titel
Variations of cohort intelligence
verfasst von
N. S. Patankar
Anand J. Kulkarni
Publikationsdatum
27.05.2017
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 6/2018
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-017-2647-y

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