In this paper, a kind of Partheno Genetic Algorithm(PGA)based on Path Representation scheme is pro-posed for solving Traveling Salesman Problem(TSP). This algorithm employs only mutation and selection operatorsto prod...In this paper, a kind of Partheno Genetic Algorithm(PGA)based on Path Representation scheme is pro-posed for solving Traveling Salesman Problem(TSP). This algorithm employs only mutation and selection operatorsto produce the offspring, instead of traditional crossover operator. A specific mutation operator is designed combiningthe insertion operator with inversion operator, which ensures its strong searching capability. This algorithm simu-lates the recurrence of nature evolution process, while providing fewer control parameters. Experiments based onChinese 144 cities(CHN144)and 7 instances selected from TSPLIB are used to test the performance of this algorithm.They prove that it can reach the satisfying optimization at a faster speed. Especially, for the CHN144, the best pathit finds is better than any other available one.展开更多
提出了一种基于蚁群优化和粒子群优化的混合算法求解TSP(Traveling Salesm an Prob lem)问题。在应用蚁群算法对TSP问题的求解过程中,利用粒子群算法对蚁群系统的参数进行优化,其目的是提高蚁群系统的优化性能,使蚁群系统的参数不必靠...提出了一种基于蚁群优化和粒子群优化的混合算法求解TSP(Traveling Salesm an Prob lem)问题。在应用蚁群算法对TSP问题的求解过程中,利用粒子群算法对蚁群系统的参数进行优化,其目的是提高蚁群系统的优化性能,使蚁群系统的参数不必靠人工经验或反复试验选取,而是通过粒子搜索自适应选取。展开更多
文摘In this paper, a kind of Partheno Genetic Algorithm(PGA)based on Path Representation scheme is pro-posed for solving Traveling Salesman Problem(TSP). This algorithm employs only mutation and selection operatorsto produce the offspring, instead of traditional crossover operator. A specific mutation operator is designed combiningthe insertion operator with inversion operator, which ensures its strong searching capability. This algorithm simu-lates the recurrence of nature evolution process, while providing fewer control parameters. Experiments based onChinese 144 cities(CHN144)and 7 instances selected from TSPLIB are used to test the performance of this algorithm.They prove that it can reach the satisfying optimization at a faster speed. Especially, for the CHN144, the best pathit finds is better than any other available one.
文摘提出了一种基于蚁群优化和粒子群优化的混合算法求解TSP(Traveling Salesm an Prob lem)问题。在应用蚁群算法对TSP问题的求解过程中,利用粒子群算法对蚁群系统的参数进行优化,其目的是提高蚁群系统的优化性能,使蚁群系统的参数不必靠人工经验或反复试验选取,而是通过粒子搜索自适应选取。
