Hybrid Genetic Algorithm And Its Application In The Assignment And Sequencing Problem

Genetic Algorithm (GA),developed by American professor J. Holland,is a sort of randomly searching algorithms which originated from the creature rule-Nature Selection and Genetic Mechanism,and has a main characteristic which is that the group searching strategy and the switching and searching for message between individuals are independent of gradient information. It especially suits to the sophisticated and no-linear problems which are difficult to the traditional methods and can be widely applied in the yields of machine learning,adaptive controlling,combinatory designing,artificial life and so on. Thus,it is one of the key techniques for intelligent computing in the 21st century.This thesis is focused on the following four topics.1. The theory of GA and its operating frame are discussed in detail.2. A new type of improved Gas-Hybrid Genetic Algorithm (HGA) is put forward,and its program is designed to solve the problem of function optimization. The computational results indicate that the performance of HGA is better than some other GAs'.3. HGA is applied to solve the assignment problem quite well. Especially,a sort of improved crossover operators-PMX is brought forward,and its responding computer program is designed.4. The mathematical mode of a sequencing problem in management system is raised and it is solved successfully by designing the responding HGA computer program.The assignment problem is a type of sophisticated combinatory designs which are difficult to be solved by the traditional methods,and so is the sequencing problem. Over these methods,GA has the advantage in solving them. Especially,HGA in the thesis is proved by simulation results to be better than some other GAs in that it absorbs their advantages. In addition,the PMX operator as well as other genetic operators for these two problems are very efficient,and so is the responding program.