A fuzzy matter-element scheme multi-objective optimization method based on genetic algorithm

Abstract

This paper presents a fuzzy matter-element optimization method for a machine scheme based on a genetic algorithm. For example, for designing a drive scheme, at first, the fuzzy matter-element is applied to build a model for the drive scheme. Then, the adaptive macroevolution genetic algorithm is applied to resolve this model during which the real number coding method is used to code chromosomes for the drive scheme. During the process of resolving the model, the rhombic thought method has been combined with the genetic algorithm organically. The paper discusses the key technology of the genetic algorithm for designing the drive scheme in detail. At last, this method is applied to design a drive scheme and a satisfying result is obtained, so the method is verified to be valid by this example.