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Hybrid discrete particle swarm optimization algorithm for capacitated vehicle routing problem

机译:容量车辆路径问题的混合离散粒子群优化算法。

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摘要

Capacitated vehicle routing problem (CVRP) is an NP-hard problem. For large-scale problems, it is quite difficult to achieve an optimal solution with traditional optimization methods due to the high computational complexity. A new hybrid approximation algorithm is developed in this work to solve the problem. In the hybrid algorithm, discrete particle swarm optimization (DPSO) combines global search and local search to search for the optimal results and simulated annealing (SA) uses certain probability to avoid being trapped in a local optimum. The computational study showed that the proposed algorithm is a feasible and effective approach for capacitated vehicle routing problem, especially for large scale problems.
机译:车辆容量限制问题(CVRP)是NP难题。对于大型问题,由于计算复杂度高,使用传统的优化方法很难获得最佳解决方案。为解决该问题,本文开发了一种新的混合逼近算法。在混合算法中,离散粒子群优化(DPSO)结合了全局搜索和局部搜索来搜索最佳结果,而模拟退火(SA)使用一定的概率来避免陷入局部最优中。计算研究表明,所提出的算法是解决车辆拥挤问题的一种可行且有效的方法,特别是对于大规模问题。

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