An multiobjective optimization method based on grey evaluation and genetic algorithms

Solving multiobjective optimization problems in many real-world domains is complicated because of insufficient data, multi-objection and multi-measurement, etc. In this paper, a multiobjective grey optimization model is suggested to describe the situation and a new method, based on the grey relational clustering analysis and genetic algorithms, is proposed to deal with the model. The simulation results demonstrate that the model is suitable and the method is effective.