[1]CHEN Jie,SHEN Yanxia,LU Xin.Artificial bee colony algorithm based on information feedback and an improved fitness value evaluation[J].CAAI Transactions on Intelligent Systems,2016,11(2):172-179.[doi:10.11992/tis.201506024]
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Artificial bee colony algorithm based on information feedback and an improved fitness value evaluation

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 11 Number of periods: 2016 2 Page number: 172-179 Column: 学术论文—机器学习 Public date: 2016-04-25
Title:
Artificial bee colony algorithm based on information feedback and an improved fitness value evaluation
Author(s):
CHEN Jie;  SHEN Yanxia;  LU Xin
Research Center of Engineering Applications for IOT, Jiangnan University, Wuxi 214122, China
Keywords:
artificial bee colony algorithm; swarm intelligence; evolutionary algorithm; function optimization; information feedback
CLC:
TP18
DOI:
10.11992/tis.201506024
Abstract:
The artificial bee colony (ABC) algorithm converges slowly and easily gets stuck on local solutions; hence, an ABC algorithm based on information feedback and an improved fitness value evaluation is proposed. The algorithm first introduces a memory mechanism for individual components to feedback information to enhance its capacity for population exploitation and to accelerate the convergence speed. Then, it adopts a new fitness function to increase the difference between individuals and to avoid premature convergence from failing to identify the best individual. Finally, the algorithm integrates an optimal nectar-source guidance mechanism into the knockout function to prevent the production of unexpected individuals. Experiments were conducted on standard functions and were compared with those with several typical improved ABCs. The results show that the improved algorithm accelerates the convergence rate and improves the solution accuracy.
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