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Metaheuristic approach for solving the vehicle routing problem: Application in pharmaceutical society

机译:元启发式方法解决车辆路径问题:在药学界的应用

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In this paper, we address the capacitated vehicle routing problem CVRP. This problem consists to optimize the itineraries of the vehicles that must do with a minimum cost and it by the use of a fleet homogeneous while respecting the constraints of time, volume and capacity However, the techniques giving the optimal path are relatively gluttonous in time of calculates when the number of customers to discover is important. So and in order to palliate to this difficulty, some methods based on meta-heuristic. are used. So we opted for the ant colony algorithm (Ant colony optimization ACO); this approach is combined with a local research to improve the gotten results. This approach is applied to a real case; the society ZEDPHARM specialized in the distribution of the pharmaceutical products the used approach is simulated by Matlab.
机译:在本文中,我们解决了车辆通行能力不足的问题CVRP。这个问题包括优化必须以最低成本完成的车辆的行程,并且通过使用均质的车队,同时考虑时间,体积和容量的限制,但是,提供最佳路径的技术在时间上相对繁琐。计算什么时候发现的客户数量很重要。因此,为了缓解这一困难,提出了一些基于元启发式的方法。被使用。因此,我们选择了蚁群算法(Ant Colony Optimization ACO);这种方法与本地研究相结合,以改善获得的结果。这种方法适用于实际情况; ZEDPHARM专门从事药品分销的协会,所使用的方法是由Matlab模拟的。

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