L-SHADE with Alternative Population Size Reduction for Unconstrained Continuous Optimization

Christopher Renkavieski, Rafael Stubs Parpinelli
2020 Anais do Computer on the Beach  
ABSTRACTDifferential Evolution (DE) is a powerful and versatile algorithmfor numerical optimization, but one of its downsides is its numberof parameters that need to be tuned. Multiple techniques have beenproposed to self-adapt DE's parameters, with L-SHADE being oneof the most well established in the literature. This work presentsthe A-SHADE algorithm, which modifies the population size reductionschema of L-SHADE, and also EB-A-SHADE, which applies amutation strategy hybridization framework to
more » ... A-SHADE. Thesealgorithms are applied to the CEC2013 benchmark set with 100dimensions, and it's shown that A-SHADE and EB-A-SHADE canachieve competitive results.
doi:10.14210/cotb.v11n1.p351-358 fatcat:e7a2oo6hkzdezpwt6a3dlivb4u