Differential Evolution Algorithm with Division of Labor
Zheng Hua Guo · Journal of Chinese Computer Systems · 2009
Differential Evolution algorithm with division of labor is proposed in this paper to overcome the drawbacks of rand/1 and best/1 mutation strategies.Combining with the properties of good local searching ability fast convergence speed of best/1 mutation strategy and the properties of good global searching ability of rand/1 mutation strategy,the algorithm employs the ideal of division of labor and give different individual different tasks.Excellent individuals choose best/1 to be charged with exploitation tasks and the other individuals choose rand/1 to be charged with exploration tasks.The algorithm's performance is improved through the cooperation of individuals with different tasks.Experiments on benchmark functions show that the proposed algorithm can improve the convergence speed and the global searching ability greatly.