Improved Whale Optimization Algorithm Based on COBL and FDB
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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