在分析现有多目标优化技术的基础上,提出了一种基于生态协同的多目标优化算法.此算法借鉴生态学中的生态种群密度竞争方程来描述多目标间的复杂关系,可以同时从个体和种群层次指导多目标之间关联程度的调整.实验结果表明，此算法更易于寻找多目标优化问题的满意解.

A multiobjective optimization using genetic algorithm based on ecological cooperation (ECGA) is proposed in this paper after analyzing the present studies. In the algorithm, an ecological population density competition equation is used for reference to describe the relation between multiple objectives and to direct the adjustment over the relation at individual and population levels. Simulation experiments prove that the algorithm has a better performance in finding the Pareto solutions.

This project is supported by the National Natural Science Foundation of China under Grant No.69971022 (国家自然科学基金), and the Youth Foundation of University of Science and Technology of China (中国科学技术大学青年基金).