基于模型的多目标优化问题方法研究  

Research on Multi-objective Optimization Method Based on Model

作　　者：刘建军 司光亚[1] 王艳正[1] 何大川[1] Liu Jianjun;Si Guangya;Wang Yanzheng;He Dachuan(National Defence University,Beijing 100091,China;XinJiangYiLi Military Subarea,Yining 835000,China)

机构地区：[1]国防大学,北京100091 [2]新疆伊犁军分区,新疆伊宁835000

出　　处：《系统仿真学报》2020年第11期2138-2145,共8页Journal of System Simulation

基　　金：国家自然科学基金(61403400)。

摘　　要：基于模型的多目标优化方法目的是创新一种通过黑箱评估的多目标函数优化算法,该算法从解空间上的混合分布中迭代生成候选解,并根据采样解的控制数来更新混合分布,求解过程的搜索偏向于Pareto最优解的集合。算法在解空间上寻找混合分布,使得混合分布的每个分量都是以帕累托最优解为中心的简并分布,并且每个预计的Pareto最优解都通过一个阈值距离均匀地分布在Pareto最优解集上,实验通过几个基准函数和方法证明了该算法的性能。There is a model-based algorithm for the optimization of multiple objective functions by means of black-box evaluation is proposed. The algorithm iteratively generates candidate solutions from a mixture distribution over the solution space and updates the mixture distribution based on the sampled solutions’ domination count, such that the future search is biased towards the set of Pareto optimal solutions. The proposed algorithm seeks to find a mixture distribution on the solution space so that each component of the mixture distribution is a degenerate distribution centered at a Pareto optimal solution and each estimated Pareto optimal solution is uniformly spread across the Pareto optimal set by a threshold distance. The performance of the proposed algorithm is verified by several benchmark problems.

关 键 词：模型 多目标优化 算法 PARETO前沿 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]