Multi-objective Firefly Algorithm based on Multi-strategy Fusion
In order to solve the problems such as weak exploration ability,poor convergence and poor distribution of multi-objective Firefly algorithm when dealing with complex optimization problems,this paper proposes a multi-objective Firefly algorithm based on multi-strategy fusion.Firstly,a combination of randomization and homogenization is used to initialize the population,ensuring the u-niformity and randomness of the initial population;Secondly,guided by the elite solution of ar-chives,the firefly movement is introduced into the firefly movement formula by introducing Levy flight random perturbation and adding mutation operators to avoid the population falling into local op-tima,balancing the algorithm's local search and de global exploration capabilities;Finally,a crow-ding distance mechanism is introduced to maintain external files to obtain evenly distributed Pareto frontiers.Comparing the MOFA-MSF algorithm with 5 classic algorithms and 7 recent algorithms,the results show that MOFA-MSF has good performance in exploration ability,convergence,and distribution.
国家科技期刊平台
NSTL
万方数据
维普
