| 求解GTSP问题的自适应遗传算法 |
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| 引用本文： | 王跃东,李卫,杨卫波.求解GTSP问题的自适应遗传算法[J].计算机工程与应用,2011,47(27):41-43. |
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| 作者姓名： | 王跃东 李卫 杨卫波 |
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| 作者单位： | 1.温州大学 瓯江学院，浙江 温州 3250272.温州出入境检验检疫局，浙江 温州 325027 |
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| 摘 要： | 利用传统遗传算法的基本思想，针对GTSP问题，提出了一种改进的自适应遗传算法。通过个体编码方法，将GTSP转化为多段图最短路径问题，采用动态规划算法求解;根据多段图最优子结构性质设计了个体适应度评价函数，加快了算法的运行速度。实验测试的结果表明，新算法比传统的遗传算法具有更快的收敛速度和更优的解质量。
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| 关 键 词： | 自适应遗传算法 动态规划算法 广义旅行商问题 |
| 修稿时间： | |
Adaptive genetic algorithm for GTSP |
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| WANG Yuedong,LI Wei,YANG Weibo.Adaptive genetic algorithm for GTSP[J].Computer Engineering and Applications,2011,47(27):41-43. |
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| Authors: | WANG Yuedong LI Wei YANG Weibo |
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| Affiliation: | 1.Oujiang College，Wenzhou University，Wenzhou，Zhejiang 325027，China2.Wenzhou Entry-exit Inspection and Quarantine Bureau，Wenzhou，Zhejiang 325027，China |
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| Abstract: | Based on the basic concepts of traditional genetic algorithm,an improved adaptive genetic algorithm for solving GTSP is proposed.GTSP is changed into multi-segment map problem which is solved with dynamic programming algorithm by individual coding.Individual fitness function based on multi-segment map optimal sub-structure is designed to speed up algorithm calculation speed.Experimental test results show that the new algorithm has faster convergence and better solution than traditional genetic algorithm. |
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| Keywords: | adaptive genetic algorithm dynamic programming algorithm Generalized Traveling Salesman Problem(GTSP) |
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