To solve the problems of Whale Optimization Algorithm(WOA),such as strong dependence on initial solution and easy to fall into local optimality,COBL and FDB Whale Optimization Algorithm(CFWOA)is proposed.Firstly,in the population initial-ization stage,a compound strategy is used to randomly generate the initial solution.Secondly,the fitness-distance balance strategy is used to update the location of new individuals in the iterative process.Finally,CFWOA is compared with the original WOA,Genetic Algorithm(GA)and Particle Swarm Optimization(PSO)through 6 benchmark test functions.The results show that CFWOA has higher search efficiency and global search ability than the other three algorithms.
Whale Optimization Algorithmcompound opposition learningfitness-distance balancebenchmark function
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