Earticle

초록

영어

Aiming at such shortcomings of traditional Bat algorithm as low precision convergence, premature convergence, slow convergence, an improved BA based on inertia weight factor and Lévy flight (ILBA) has been proposed, which has made two modifications on update equations of bat flying position in BA, using inertia weight factor to keep the flight inertia of bat individual, adaptively adjust the exploitation mechanism of the algorithm in different iteration periods, make the algorithm achieve better convergence precision and altering the strategy about position update of bats from Brownian random walks into Lévy flights strategy to effectively avoid local optimism of the algorithm and guarantee its exploration mechanism while taking advantage of heavy-tailed effect of Lévy flight to speed up the convergence. By means of 4 typical test functions simulation, the results show that ILBA boasts faster convergence and superior optimal performance compared to traditional BA and LBA.

목차

Abstract
 1. Introduction
 2. Bat Algorithm
  2.1. Preying of Bats
  2.2. BA Steps
 3. BA with Inertia Factor and Lévy Flight Strategy
  3.1. Inertia Factor
  3.2. Lévy Flight Strategy
 4. Simulations
  4.1. Standard Test Functions
  4.2. Setting the Algorithm Parameters
  4.3. Analysis of Experimental Results
 5. Conclusions
 References

키워드

저자

• Ma weifeng [ School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, China ]
• Shi Hao [ Hangzhou Cropsoft Science & Technology Co., Ltd., Hangzhou, China ]
• Sun Xiaoyong [ School of Information and Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Multimedia and Ubiquitous Engineering

• 간기

  월간

• pISSN

  1975-0080

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605