A New Teaching–Learning-based Chicken Swarm Optimization Algorithm

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Journal Title
Journal ISSN
Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Date
2019
Major/Subject
Mcode
Degree programme
Language
en
Pages
19
Series
Soft Computing
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.
Description
Keywords
Algorithm, Benchmark, Chicken Swarm Optimization, Function, Hybrid, Teaching–Learning-based Optimization
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Citation
Deb , S , Gao , X Z , Tammi , K , Kalita , K & Mahanta , P 2019 , ' A New Teaching–Learning-based Chicken Swarm Optimization Algorithm ' , Soft Computing . https://doi.org/10.1007/s00500-019-04280-0