关键词: 动态多目标优化, 自适应迁移策略, 预测策略, 差分演化算法

Abstract: In order to solve the problem of searching and tracing the Pareto Optimal Front （POF） and Pareto Optimal Set （POS）, two strategies are investigated. The adaptive immigration strategy is designed to improve the diversity of the population by adaptively inserting the immigrations according to the changed environments, thus can improve the adaptability to the environments. The prediction strategy is used to quickly trace POF by the prediction population which is established by the time series and some disturbances. The two strategies are introduced into differential evolution to solve the dynamic multi-objective problems. The experimental results show that the adaptive and prediction strategies based differential evolution shows great ability to adapt to the changed environments and can find POS quickly.

Key words: dynamic multi-objective optimization, adaptive immigration strategy, prediction strategy, differential evolution