Fruit fly optimization algorithm with adaptive mutation
Chengzhong Liu · Jisuanji yingyong yanjiu · 2013
In order to overcome the problems of low convergence precision and easily relapsing into local extremum in basic fruit fly optimization algorithm(FOA),this paper presented an adaptive mutation fruit fly optimization algorithm(FOAAM).During the evolution,in the condition of basic FOA's trapping in local extremum judging from the population's fitness variance and the current optimal,first,it generated M current optimal replicates.Then,it disturbed replicates by a certain probability P Gauss mutation operator.Finally,it optimized mutated replicates again to jump out of local extremum and continue to optimize.Experimental results show that the new algorithm has the advantages of better global searching ability,speeder convergence and more precise convergence.