中文摘要：

宏观进化多目标遗传算法macro．evolutionarymulti．objectivegeneticalgoritIlm，简称MMGA），是一种新的高等物种进化算法，它可以避免传统遗传算法（geneticalgorithm，简称CA）在选择过程中出现的早熟收敛现象。MMGA是综合宏观进行化算法macro—evolutionaryalgorithm，简称MA）与GA而形成的，该算法的特点是引进了MA算法中的种群间关联矩阵。利用种群间的适应度信息和个体间的距离信息，能够保持种群的多样性，为解决多目标规划问题提供了一条新的途径。本文将介绍MMGA算法的原理及步骤，并将其用到水库多目标优化调度中。

英文摘要：

Macro-evolutionary multi-objective genetic algorithm is a new kind of algorithm inspired by the high-level species evolution, which can avoid the premature convergence that arise during the selection process of conventional GA. MMGA is an integration of macro-evolutionary algorithm（MA） and genetic algorithm（GA）. By introducing it into the connectivity matrix W between species in MA, it can utilize the fitness information between species and the distance information between individuals. Consequently the diversity of the solutions can be maintained, thus provides a new alternative to solve the multi-objective optimization problem. The principle and solution step of MMGA is introduced and applied to the multi-objective optimization of reservoir operation.