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首页> 外文期刊>European Journal of Operational Research >Using greedy clustering method to solve capacitated location-routing problem with fuzzy demands
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Using greedy clustering method to solve capacitated location-routing problem with fuzzy demands

机译：用贪婪聚类法求解模糊需求下的带容量选路问题

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摘要

In this paper, the capacitated location-routing problem with fuzzy demands (CLRP-FD) is considered. In CLRP-FD, facility location problem (FLP) and vehicle routing problem (VRP) are observed simultaneously. Indeed, the vehicles and the depots have a predefined capacity to serve the customers that have fuzzy demands. To model this problem, a fuzzy chance constrained programming model of that is designed based upon the fuzzy credibility theory. To solve this problem, a greedy clustering method (GCM) including the stochastic simulation is proposed. To obtain the best value of the dispatcher preference index of the model and to analyze its influence on the final solution, numerical experiments are carried out. Finally, to show the performance of the greedy clustering method, associated results are compared with the lower bound of the solutions.
机译：在本文中，考虑了带有模糊需求的功能性位置路由问题（CLRP-FD）。在CLRP-FD中，同时观察到设施位置问题（FLP）和车辆路线问题（VRP）。实际上，车辆和仓库具有预定的能力，可以为有模糊需求的客户提供服务。为了对此问题建模，基于模糊可信度理论设计了模糊机会约束规划模型。为了解决这个问题，提出了一种包含随机模拟的贪婪聚类方法。为了获得模型的调度程序偏好指数的最佳值并分析其对最终解决方案的影响，进行了数值实验。最后，为了显示贪婪聚类方法的性能，将相关结果与解决方案的下限进行了比较。

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