Abstract
目标维数较高的多目标优化问题的难题在于非支配解急剧增加,经典算法由于缺乏足够的选择压力导致性能急剧下降.提出了基于偏好等级的免疫记忆克隆选择优化算法,用于解决目标维数较高的多目标优化问题.利用决策者提供的偏好信息来为抗体分配偏好等级,根据该值比例克隆抗体,增大抗体的选择压力,加快收敛速率.根据偏好信息来缩减Pareto前沿,并用有限的偏好解估计该前沿.同时,建立了免疫记忆种群来保留较好的非支配抗体,采用ε支配机制来保持记忆抗体种群的多样性.实验结果表明,对于2目标的偏好多目标问题以及高达8目标的DTLZ2和DTLZ3问题,该算法取得了一定的实验效果.
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