基于径向空间划分的昂贵多目标进化算法  

Expensive Many-objective Evolutionary Algorithm Based on Radial Space Division

作　　者：顾清华[1,2] 周煜丰 李学现 阮顺领[2] GU Qing-Hua;ZHOU Yu-Feng;LI Xue-Xian;RUAN Shun-Ling(School of Management,Xi'an University of Architecture and Technology,Xi'an 710055;School of Resource Engineering,Xi'an University of Architecture and Technology,Xi'an 710055)

机构地区：[1]西安建筑科技大学管理学院,西安710055 [2]西安建筑科技大学资源工程学院,西安710055

出　　处：《自动化学报》2022年第10期2564-2584,共21页Acta Automatica Sinica

基　　金：国家自然科学基金(51774228,51864046);陕西省自然科学基金杰出青年项目(2020JC-44)资助。

摘　　要：为了解决难以建立精确数学模型或者真实评估实验成本高昂的多目标优化问题,提出了一种基于径向空间划分的昂贵多目标进化算法.首先算法使用高斯回归作为代理模型逼近目标函数;然后将目标空间的个体投影到径向空间,结合目标空间和径向空间信息保留对种群贡献更高的个体;之后由径向空间中个体的位置分布决定下一步应该选择哪些个体进行真实评估;最后,采用一种双档案管理策略维护代理模型的质量.数值实验和现实问题上的结果表明,与5种先进算法相比,该算法在解决昂贵多目标优化问题时能够提供更高质量的解.In order to solve the problem of many-objective optimization that it is difficult to establish an accurate mathematical model or the actual evaluation experiment is expensive, an expensive many-objective evolutionary algorithm based on radial space division is proposed. First, the algorithm uses Gaussian regression as a surrogate model to approximate the objective function;Second the individuals in the objective space are projected to the radial space, and the individuals with higher contributions to the population are retained through the objective space and radial space information;Third the position distribution of the individuals in the radial space determines which individuals should be selected for real evaluation in the next step;Finally, a double archives management strategy is adopted to maintain the quality of the surrogate model. The results of numerical experiments and real problems show that compared with five advanced algorithms, the algorithm proposed in this paper can provide higher quality solutions when solving expensive many-objective optimization problems.

关 键 词：昂贵多目标优化问题 高斯过程 径向投影 双档案管理策略 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]