A new integrated design method based on fuzzy matter-element optimization

Abstract

This paper puts forward a new integrated design method based on fuzzy matter-element optimization. On the based of analyzing the model of multi-objective fuzzy matter-element R̃, the paper defines the matter-element weighting and changes solving a multi-objective fuzzy optimization into solving a dependent function K( x) of the single-objective optimization according to the optimization criterion. The paper particularly describes the realization approach of the GA process of multi-objective fuzzy matter-element optimization: encode, produce initial population, confirm fitness function, select operator, etc. In the process, the adaptive macro genetic algorithms (AMGA) are applied to enhance the evolution speed. The paper improves the two genetic operators: cross-over and mutation operator. The modified adaptive macro genetic algorithms (MAMGA) are put forward simultaneously, and adopted to solve the optimization problem. Three optimization methods, namely the fuzzy matter-element optimization method, the linearity weighted method and the fuzzy optimization method, are compared using tables and figures, showing that not only is MAMGA a little better than AMGA, but also it reaches the extent to which the effective iteration generation is 62.2% of simple genetic algorithms (SGA). By the calculation of an optimum example, the improved genetics method of reported in the paper is much better than the methods in the references of the paper.