Evolutionary Algorithm for Dynamic Multi-Objective Optimization Problems and Its Convergence
Yuping Wang · Dianzi xuebao · 2007
A method for dynamic multi-objective optimization problems(DMOPs)is given.First,we divide the time period into several equal subperiods.In each subperiod(termed as environment),the static rank variance and the static density variance of the population are defined,thus the DMOPs is transformed into several bi-objective static optimization problems by using the static rank variance and the static density variance.Then,based on a new mutation operator which can automatically check out the environment variation,a dynamic multi-objective evolutionary algorithm is proposed and the convergence analysis of the algorithm is presented.Finally the numerical results demonstrate the effectiveness of the new algorithm.