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A Novel Hybrid Bat Algorithm with Differential Evolution Strategy for Constrained Optimization

Xianbing Meng, X. Z. Gao, Yu Liu

보안공학연구지원센터(IJHIT) International Journal of Hybrid Information Technology Vol.8 No.1 2015.01 pp.383-396

※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

A novel hybrid Bat Algorithm (BA) with the Differential Evolution (DE) strategy using the feasibility-based rules, namely BADE is proposed to deal with the constrained optimization problems. The sound interferences induced by other things are inevitable for the bats which rely on the echolocation to detect and localize the things. Through integration of the DE strategy with BA, the insects’ interferences for the bats can be effectively mimicked by BADE. Moreover, the bats swarm’ mean velocity is simulated as the other bats’ effects on each bat. Having considered the living environments the bats inhabit, the virtual bats can be lifelike. Experiments on some benchmark problems and engineering designs demonstrate that BADE performs more efficient, accurate, and robust than the original BA, DE, and some other optimization methods.

 
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