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

摘要

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.