Genetic Algorithms Based on Fuzzy Evaluation for Multicriterion Function Optimization
基于模糊优选的多目标优化遗传算法

The paper summarizes the traditional methods for multicriterion function optimization and introduces some genetic strategies for multicriterion function optimization. In order to solve the problem more efficiently, we incorporate new fuzzy evaluation technique into genetic algorithm to replace the fitness function. The new model is proved to be correct in theory and an example of function optimization with two objectives is given at the end of the paper which shows that the new model is very efficient.