Research on Chaos Partheno -Genetic Algorithm for TSP
Traveling Salesman Problem (TSP) is a typical combination optimization problem; it is hard to find a precision result So it is very important to search for the near result. A novel chaos partheno-genetic algorithm (CPGA) method is proposed for TSP in this paper. The new legal solution is obtained by chaos search, partheno-genetic algorithm and greedy local search. Partheno-genetic algorithm overcomes the premature convergence drawback of genetic algorithms, and which is guaranteed to keep the diversity of the population in the conditions of the lower diversifying initial population. Moreover, the algorithm not only makes use the chaos search strategy to improve the algorithm search space greatly and avoid the standard genetic algorithms easy falling into the partial minimum flaw, but also utilizes the greedy local search to improve local searching capability, enhance searching efficiency. In the process of optimization, the method has the ability of escaping from the local minimized point and arriving at the global optimal point. Simulation results show that the chaos partheno-genetic algorithm using for TSP are efficient and feasible.
chaos search partheno-genetic algorithm greedy local search TSP
Ren Shuai Wang Jing Xuejun Zhang
National Engineer Research Center of Advanced Rolling, University of Science and Technology Beijing, USTB Beijing, China
国际会议
太原
英文
290-293
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）