An evolutionary algorithm for dynamic multi-objective optimization
作者： Yuping Wang , Chuangyin Dang , None
DOI: 10.1016/J.AMC.2008.05.151
关键词:
摘要: In this paper, the dynamic multi-objective optimization problem (DMOP) is first approximated by a series of static problems (SMOPs) dividing time period into several equal subperiods. each subperiod, seen as taking parameter fixed. Then, to decrease amount computation and efficiently solve problems, transformed two-objective based on two re-defined objectives. Finally, new crossover operator mutation adapting environment changing are designed. Based these techniques, evolutionary algorithm proposed. The simulation results indicate that proposed can effectively track varying Pareto fronts with time.
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