基于遗传算法的多目标问题求解方法

New method for solving multi-objective problem based on genetic algorithm

本文利用遗传算法进化过程中每代种群均生成大量可行解的特点,提出一种基于目标序列的排序矩阵评价个体适应度的多目标遗传算法,改进了遗传算法的参数确定方法,有效控制了非劣解集的替换选取过程,使得算法可以一次交互求得非劣解集。最后将该方法应用于供水和发电的综合利用水库的多目标调度中,验证了其可行性。

A new multiobjective genetic algorithm based on the variety of plentiful solution in every generation of the evolution is proposed, by which the Pareto set can be searched by calculation of only one time interchange.The appraising function in this method ranks the gene by comparing their performance in each objective function through the sorting matrix created by the objective function. In order to elevate the efficiency of this method, the parameter's calibration is improved and the Pareto solution's selection is controlled effectively.The application in a multiobjective reservoir's longterm optimal operation for power generation and water supply is given as an example to demonstrate the feasibility of this method.