Stir strategy based on multi-objective evolutionary algorithm
Hongmei Li · Jisuanji gongcheng yu sheji · 2008
Capable of searching for multiple Pareto optimal solutions concurrently in a single simulation run,and the current research work focuses on the Pareto optimal-based MOO evolutionary approaches.The intensive degree is defined and used to maintain a good spread of solution in the population,and define the fitness of the individual through Pareto strength and intensive degree,and given the stir strategy,which results in a new population significantly indifferent from the old one while inheriting the evolutionary information from the history,by this way,the performance on global convergence is enhanced,and premature is avoided simultaneously.Test results show that the new approach is feasible and effective.