A novel bat algorithm with habitat selection and Doppler effect in echoes for optimization

Xian Bing Meng*, X. Z. Gao, Yu Liu, Hengzhen Zhang

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

140 Citations (Scopus)

Abstract

A novel bat algorithm (NBA) is proposed for optimization in this paper, which focuses on further mimicking the bats' behaviors and improving bat algorithm (BA) in view of biology. The proposed algorithm incorporates the bats' habitat selection and their self-adaptive compensation for Doppler effect in echoes into the basic BA. The bats' habitat selection is modeled as the selection between their quantum behaviors and mechanical behaviors. Having considered the bats' self-adaptive compensation for Doppler effect in echoes and the individual's difference in the compensation rate, the echolocation characteristics of bats can be further simulated in NBA. A self-adaptive local search strategy is also embedded into NBA. Simulations and comparisons based on twenty benchmark problems and four real-world engineering designs demonstrate the effectiveness, efficiency and stability of NBA compared with the basic BA and some well-known algorithms, and suggest that to improve algorithm based on biological basis should be very efficient. Further research topics are also discussed.

Original languageEnglish
Pages (from-to)6350-6364
Number of pages15
JournalEXPERT SYSTEMS WITH APPLICATIONS
Volume42
Issue number17-18
DOIs
Publication statusPublished - 16 May 2015
MoE publication typeA1 Journal article-refereed

Keywords

  • Bat Algorithm
  • Doppler effect in echoes
  • Habitat selection
  • Mechanical behavior
  • Optimization
  • Quantum behavior

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