中文摘要：

针对国家电网制定的考核方案经常变动，考核单位无法合理分配公司资源的问题，对指标进行高维多目标优化建模，得出一些总体得分较高的资源分配方案供决策者选择。本文针对此模型选用最小二乘法的高维多目标减少算法来去除冗余目标，同时引入一种新的密度评估函数来更有效地收敛到Pareto前沿。实验引用新的密度评估函数NSGA-II算法，且与原NSGA-II算法进行比较。实验结果证明了该模型的有效性和合理性。

英文摘要：

The assessment plan developed by state grid changes so frequently that the company under assessment can not allocate its resources reasonably. The paper proposes a high-dimensional multi-objective optimization modeling method based on indicators in the assessment plan, which aims to make the company achieve some resource allocation scheme which have higher overall score without taking the impact of weighting factors. In the model, the least squares based high-dimensional multi-objective reduction algorithm is used to eliminate redundant objectives and a novel density assessment function is introduced to make more effectively converge to the Pareto front. Experimental reference new density evaluation functions of the NSGA-II algorithm, and compare with the original NSGA-II. Results demonstrate the validity and legitimacy of the proposed model.