Improving the local search capability of Effective Butterfly Optimizer using Covariance Matrix Adapted Retreat Phase

Effective Butterfly Optimizer(EBO) is a self-adaptive Butterfly Optimizer which incorporates a crossover operator in Perching and Patrolling to increase the diversity of the population. This paper proposes a new retreat phase called Covariance Matrix Adapted Retreat Phase (CMAR), which uses covarian...

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Bibliographic Details
Published in2017 IEEE Congress on Evolutionary Computation (CEC) pp. 1835 - 1842
Main Authors Kumar, Abhishek, Misra, Rakesh Kumar, Singh, Devender
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2017
Subjects
Covariance matrices
Electrical engineering
Heuristic algorithms
Mathematical model
Optimization
Sociology
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Summary:Effective Butterfly Optimizer(EBO) is a self-adaptive Butterfly Optimizer which incorporates a crossover operator in Perching and Patrolling to increase the diversity of the population. This paper proposes a new retreat phase called Covariance Matrix Adapted Retreat Phase (CMAR), which uses covariance matrix to generate a new solution and thus improves the local search capability of EBO. This version of EBO is called EBOwithCMAR. We evaluated the performance of EBOwithCMAR on CEC-2017 benchmark problems and compared with the results of winners of a special session of CEC-2016 for bound-constrained problems. The experimental results show that EBOwithCMAR is competitive with the compared algorithms.
DOI:10.1109/CEC.2017.7969524