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Solving Chinese Traveling Salesman Problem with Improved Genetic Algorithms

Pan Lideng;Huang Xiaofeng(Department of Chemical Automation. Beijing University of Chemical Technology, Beijing, 100029)  
Genetic Algorithms (GAs)are general-purposeeglobal optimization algorithmsbased on natural evolution rinciple In thisspaple, focusing on a kind of NP completecombinahon optimum problem--Travelling Salesman Problem (TSP), exchange operatorand simulated annealing method are introduced into GAs to approve optimum efficiency.UP to now, the best result of Chinese, TSP is 15 426 km. Only distances between all the cities are used in the improved GAs, and an even better result, 15 409 km,has been obtained.
【CateGory Index】: O224
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