Genetic Algorithms Based on Fuzzy Evaluation for Multicriterion function Optimization

The paper introduces some genetic strategies for multicriterion function optimization. In order to solve the problem more efficiently, the authors incorporate new fuzzy evaluation technique into genetic algorithm to replace the fitness function. At the end of the paper an example of function optimization with two objectives is given which shows that the new model is very efficient.