大学毕业设计论文-遗传算法及其应用浅析论文.docVIP

专业选修课期末考核（） 学 院： 专 业： 班 级： 学 号： 学生姓名： 指导教师： 2015年 6 月 1 日 贵州大学论文（设计） 诚信责任书 本人郑重声明：本人所呈交的毕业论文（设计），是在导师的指导下独立进行研究所完成。毕业论文（设计）中凡引用他人已经发表或未发表的成果、数据、观点等，均已明确注明出处。 特此声明。 论文（设计）作者签名： 日 期： 【Abstract】Genetic Algorithm (based Algorithm, GA) is developed rapidly in recent years a new kind of random search and optimization Algorithm, is a kind of reference for biological mechanism of natural selection and evolution of highly parallel, randomized, adaptive search Algorithm. Its research history is shorter, the early is an attempt to explain complex adaptive process of creatures in nature system, simulation of the evolution mechanism to construct the model of artificial system. Range of evolutionary computation in the world in recent years, computational intelligence has as an important direction of artificial intelligence research, and later the artificial life research, genetic algorithm has been widely attention. Its basic idea is based on Darwins theory of evolution and Mendels genetics. The widespread use of genetic algorithm and the development potential has led many scholars in-depth study genetic algorithm, and has published many books about it. The TSP problem is a classic problem of ancient, studies of hundreds of years. TSP traveling salesman problem is a typical NP complete problem, genetic algorithm is an ideal method to solve the problem of NP. This paper firstly introduces the basic principle of genetic algorithm, genetic algorithm, the characteristics of the development direction of genetic algorithm and the main application field; Then in view of the problems this paper discusses the genetic algorithm (ga) said in coding and genetic operators (including selection operator, crossover operator, mutation operator) and so on, the application of simple discuss several encoding methods, finally introduces the TSP problem. 【keywoeds】Genetic Algorithm;TSP;genetic opera