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针对多目标遗传算法存在的缺陷,提出了基于改进混沌优化的多目标遗传算法.引入基于改进Tent映射的自适应变尺度混沌优化方法细化搜索空间和高效寻优,结合非支配排序的群体分级机制和精英保留等多目标优化策略,保持种群多样性的同时保证了进化向Pareto最优解集的方向进行.多目标测试函数的数值仿真和电力系统无功优化的算例分析表明了该算法的有效性和可行性.
Aiming at the shortcomings of multi-objective genetic algorithm, a multi-objective genetic algorithm based on improved chaotic optimization is proposed.An improved scale-based chaotic optimization method based on improved Tent mapping is proposed to refine the search space and optimize efficiently, combining with non-dominated sorting group classification Mechanism and elite reservation, and so on, to keep the diversity of population while ensuring the evolution to the direction of Pareto optimal solution set.Multi-objective test function numerical simulation and power system reactive power optimization case study shows that the algorithm Effectiveness and feasibility