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A swap sequence based Artificial Bee Colony algorithm for Traveling Salesman Problem

机译:基于交换序列的人工蜂殖民地群体群体问题

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In this research paper, Artificial Bee Colony algorithm is modified with multiple update rules and K-opt operation to solve the Traveling Salesman Problem. Here the features of swap sequences and swap operations on the sequence of cities (solution/path) of the problem are used to create different solution (path) update rules of the algorithm. Eight different rules are proposed to update solutions in the algorithm. Updation of a solution by an employed bee or by an onlooker bee is done by a randomly selected rule from the rule set using Roulette Wheel selection process. In the scout bee phase of the algorithm, the perturbation technique, K-opt operation is applied on any stagnant solution for a fixed number of times for the possible improvement of it. The K-opt operation is again used at the end of the search process to improve the quality of the final solution (if possible). Proposed method is tested with a set of benchmark test problems from TSPLIB and it is observed that the efficiency of the algorithm is adequate with respect to the accuracy and the consistency for solving standard TSPs (Symmetric as well as Asymmetric) compared to the existing algorithms in the literature.
机译:在本研究论文中,用多个更新规则和K-OPT操作进行了修改人工蜂菌落算法,以解决旅行推销员问题。这里,问题的交换序列和交换操作的功能用于创建算法的不同解决方案(路径)更新规则。提出了八种不同的规则来更新算法中的解决方案。使用Roulette Wheel选择过程的规则集的随机选择的规则来更新雇用的蜂或旁观者蜜蜂的更新。在算法的SCOUT BEE相中,扰动技术,K-opt操作在任何停滞溶液上施加,用于固定的次数,以便可能改善它。在搜索过程结束时再次使用K-OPT操作以提高最终解决方案的质量(如果可能的话)。用来自TSPLIB的一组基准测试问题测试了所提出的方法,观察到与现有算法相比,算法的效率是足够的,用于求解标准TSPS(对称的TSPS(对称和不对称)的准确性和一致性文献。

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