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  • 标题:A Novel Hybrid Bat Algorithm with Differential Evolution Strategy for Constrained Optimization
  • 本地全文:下载
  • 作者:Xianbing Meng ; X. Z. Gao ; Yu Liu
  • 期刊名称:International Journal of Hybrid Information Technology
  • 印刷版ISSN:1738-9968
  • 出版年度:2015
  • 卷号:8
  • 期号:1
  • 页码:383-396
  • DOI:10.14257/ijhit.2015.8.1.34
  • 出版社:SERSC
  • 摘要: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.
  • 关键词:Bat Algorithm (BA); Differential Evolution (DE); feasibility-based rules; ; constrained optimization
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