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New Mechanism of Combination Crossover Operators in Genetic Algorithm for Solving the Traveling Salesman Problem

机译:解决旅行推销员问题遗传算法中组合交叉运算符的新机制

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Traveling salesman problem (TSP) is a well-known in computing field. There are many researches to improve the genetic algorithm for solving TSP. In this paper, we propose two new crossover operators and new mechanism of combination crossover operators in genetic algorithm for solving TSP. We experimented on TSP instances from TSP-Lib and compared the results of proposed algorithm with genetic algorithm(GA), which used MSCX. Experimental results show that, our proposed algorithm is better than the GA using MSCX on the min, mean cost values.
机译:旅行推销员问题(TSP)是一个众所周知的计算领域。有许多研究来改善求解TSP的遗传算法。在本文中,我们提出了两个新的交叉运营商和求解TSP的遗传算法中组合交叉运算符的新机制。我们从TSP-lib进行了TSP实例,并将提出的遗传算法(GA)与使用MSCX进行了比较了所提出的算法的结果。实验结果表明,我们所提出的算法比MIN的MSCX在MSCX上更好,平均成本值更好。

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