计算机工程与应用 ›› 2017, Vol. 53 ›› Issue (14): 148-154.DOI: 10.3778/j.issn.1002-8331.1701-0249

• 模式识别与人工智能 • 上一篇    下一篇

四点三线遗传算法求解旅行商问题

郑  明1,2,3,卓慕瑰1,2   

  1. 1.梧州学院 广西高校行业软件技术重点实验室,广西 梧州 543002
    2.梧州学院 信息与电子工程学院,广西 梧州 543002
    3.吉林大学 计算机科学与技术学院,长春 130012
  • 出版日期:2017-07-15 发布日期:2017-08-01

Solution for traveling salesman problem with four vertices and three lines genetic algorithm

ZHENG Ming1,2,3, ZHUO Mugui1,2   

  1. 1.Guangxi Colleges and Universities Key Laboratory of Professional Software Technology, Wuzhou University, Wuzhou, Guangxi 543002, China
    2.College of Information and Electronic Engineering, Wuzhou University, Wuzhou, Guangxi 543002, China
    3.College of Computer Science and Technology, Jilin University, Changchun 130012, China
  • Online:2017-07-15 Published:2017-08-01

摘要: 为解决NP完全的旅行商问题,提出一种四点三线遗传算法。该算法特色在两阶段策略,第一阶段是变异算子优化,将汉密尔顿环中所有大于两点的内部路径倒置,并用新极值代替原极值。第二阶段是四点三线优化,将汉密尔顿环分为n个四点三线局部路径并将每个局部路径转化为最优局部路径,将所有局部路径长度求和除以1/3。交叉算子结束后,如子代含有重复位点,将未交叉部分重复位点与交叉部分重复位点对应的父代等位点交换。通过将该算法与传统遗传算法及只进行第一步优化的遗传算法进行比较,采用TSPLIB数据库实例数据,证明该算法有更高的执行效率,有更强的收敛性,适合寻找最短TSP路径。

关键词: 遗传算法, 旅行商问题, 两阶段策略, 四点三线

Abstract: A Four Vertices and Three Lines Genetic Algorithm (4V3LGA) is proposed to resolve the traveling salesman problem, which is proven to be NP-complete. The special part of the proposed algorithm is two-phase strategies. The first local optimization strategy is the mutation operator, which is executed to reverse every Local Hamiltonian Path (LHP). Every LHP contains more than 2 vertices and generates the shorter Hamiltonian Cycles (HC). The second local optimization is HC segmentation, which is executed to divide HC to n four vertices and three lines LHPs to generate the shorter HC. The sum of the LHPs is divided by 1/3. After crossover, if the positions in offspring HCs are the same, the duplicated positions of un-exchanged part are exchanged with the same positions of the father HCs of exchanged part. To prove the efficiency of the 4V3LGA proposed, traditional GA and first-phase GA are used to compare with the proposed algorithm. TSPLIB instances are used in the experiments. The computation results show that the proposed algorithm can find the better approximate solutions than other two algorithms. It can be used to find shorter TSP HC.

Key words: genetic algorithm, traveling salesman problem, two-phase strategies, four vertices and three lines