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Application of Discrete Whale Optimization Hybrid Algorithm in Multiple Travelling Salesmen Problem

机译:离散鲸鱼优化混合算法在多旅行商问题中的应用。

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For the standard whale optimization algorithm cannot directly solve the multiple travelling salesmen problem(MTSP), this paper proposes a discrete whale optimization hybrid algorithm (DWOHA) . A small amount of optimization of ant colony optimization is used to provide some elite individuals for the initial population to reduce the number of global searches. Propose a principal and subordinate chromosome coding method with smaller solution space to reduce the space complexity of the algorithm and improve the efficiency of optimization. Redefine the operation rules to apply the characteristics of MTSP discrete solution space based on the whale's unique location update method. Construct a triangular neighborhood structure to increase the local mining efficiency of the algorithm and improve the convergence accuracy. Through simulation experiments on several test sets, the results are compared with other algorithms which proves that DWOHA has an excellent performance in solving MTSP.
机译:针对标准鲸鱼优化算法不能直接解决多商贩问题(MTSP)的问题,提出了一种离散鲸鱼优化混合算法(DWOHA)。蚁群优化的少量优化用于为初始种群提供一些精英个体,以减少全局搜索的数量。提出一种解决方案空间较小的主从染色体编码方法,以减少算法的空间复杂度,提高优化效率。根据鲸鱼的唯一位置更新方法,重新定义操作规则以应用MTSP离散解决方案空间的特征。构造三角形邻域结构以提高算法的局部挖掘效率,提高收敛精度。通过在多个测试集上进行的仿真实验,将结果与其他算法进行比较,证明DWOHA在解决MTSP方面具有出色的性能。

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