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

机译:解决车辆路径问题的成立方法:在制药学会中的应用

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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,我们解决了电容车辆路由问题CVRP。这个问题在于优化必须用最低成本和使用舰队均匀的车辆的行程,同时尊重时间,体积和容量,但是,给出最佳路径的技术在时间内相对贪得无际计算顾客的数量很重要时。所以,为了使这个困难,一些基于元启发式的方法。使用。所以我们选择了蚁群算法(蚁群优化ACO);这种方法与当地的研究相结合,以改善得到的结果。这种方法适用于实际情况; ZEDPHARM专门从事药品分发的ZEDPHARM使用的方法由MATLAB模拟。

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