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Soft Computing

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19.08.2019 | Methodologies and Application

A New Teaching–Learning-based Chicken Swarm Optimization Algorithm

verfasst von: Sanchari Deb, Xiao-Zhi Gao, Kari Tammi, Karuna Kalita, Pinakeswar Mahanta

Erschienen in: Soft Computing | Ausgabe 7/2020

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Abstract

Chicken Swarm Optimization (CSO) is a novel swarm intelligence-based algorithm known for its good performance on many benchmark functions as well as real-world optimization problems. However, it is observed that CSO sometimes gets trapped in local optima. This work proposes an improved version of the CSO algorithm with modified update equation of the roosters and a novel constraint-handling mechanism. Further, the work also proposes synergy of the improved version of CSO with Teaching–Learning-based Optimization (TLBO) algorithm. The proposed ICSOTLBO algorithm possesses the strengths of both CSO and TLBO. The efficacy of the proposed algorithm is tested on eight basic benchmark functions, fifteen computationally expensive benchmark functions as well as two real-world problems. Further, the performance of ICSOTLBO is also compared with a number of state-of-the-art algorithms. It is observed that the proposed algorithm performs better than or as good as many of the existing algorithms.

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Titel: A New Teaching–Learning-based Chicken Swarm Optimization Algorithm
verfasst von: Sanchari Deb
Xiao-Zhi Gao
Kari Tammi
Karuna Kalita
Pinakeswar Mahanta
Publikationsdatum: 19.08.2019
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 7/2020
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-019-04280-0

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