[1]ZHAO Jia,CHEN Dandan,XIAO Renbin,et al.A heterogeneous variation firefly algorithm with maximin strategy[J].CAAI Transactions on Intelligent Systems,2022,17(1):116-130.[doi:10.11992/tis.202106018]
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A heterogeneous variation firefly algorithm with maximin strategy

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 17 Number of periods: 2022 1 Page number: 116-130 Column: 学术论文—人工智能基础 Public date: 2022-01-05
Title:
A heterogeneous variation firefly algorithm with maximin strategy
Author(s):
ZHAO Jia1;  CHEN Dandan1;  XIAO Renbin2;  FAN Tanghuai1
1. School of Information Engineering, Nanchang Institute of Technology, Nanchang 330099, China;
2. School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan 430074, China
Keywords:
firefly algorithm; multi-objective optimization; Pareto optimality; Maximin strategy; heterogeneous variation; exploration; convergence; diversity
CLC:
TP242
DOI:
10.11992/tis.202106018
Abstract:
Aiming at weak exploration ability and poor solving accuracy of multi-objective firefly algorithms, a heterogeneous variation firefly algorithm with maximin strategy (HVFA-M) is proposed in this paper. Firstly, the Maximin strategy is introduced to realize dynamic adjustment of external archive and random selection of elite solutions; Secondly, the elite solutions guide the firefly global search together with the current best solution to expand the search range and improve the exploration ability of the algorithm, so as to increase the probability of finding the global optimal solution; Finally, on the basis of comprehensive exploration of the algorithm, the heterogeneous variation operator is added to make the algorithm integrate the idea of local search to guide the population to carry out local mining, so as to further enhance the optimization ability of the algorithm. By comparing HVFA-M with the classical and recent multi-objective evolutionary algorithms, the experimental results show that HVFA-M can effectively improve the exploration ability of the algorithm, and also shows good performance in the convergence and diversity of solutions.
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