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《Journal of Northeast Normal University(Natural Science Edition)》 2014-01
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Applied research on genetic algorithm based on simulated annealing of constrained traveling salesman problem

KONG Ling-yi;School of Management Engineering,Xi'an University of Post and Telecommunications;  
Traveling salesman problem(TSP)was demonstrated to be non-deterministic polynomial complete problem,let alone unconnected graph constraint.In consideration of premature convergence and redundant iteration of the existing genetic algorithm,a new genetic algorithm based on simulated annealing was designed as an optimization algorithm.It employed order of places where traveling salesman went by as codes.Greedy transformation was mixed during initialization to realize local optimization,prevent a great quantity of inferior individuals emerging and increase evolution productiveness during the follow-up process.The specific fitness function was also deduced based on conditions of unconnected graph constraint.After that,the new genetic algorithm chose currently highefficiency crossover and variation arithmetic,blending in new daughter adoption criterion based on simulated annealing algorithm.Lastly,information of some cities in our country was quoted to examine the new genetic algorithm.It was found that the new genetic algorithm was notably superior to the existing GA.
【Fund】: 国家自然科学基金资助项目(71102149);; 教育部人文社会科学研究项目(12YJC790084);; 陕西省教育厅科研计划项目(12JK0056);; 西安邮电大学青年教师科研基金资助项目(ZL2011-22);; 陕西省体育局常规课题项目(12092)
【CateGory Index】: TP18
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