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Optimizing capacity, pricing and location decisions on a congested network with balking

机译:通过阻塞来优化拥塞网络上的容量,价格和位置决策

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In this paper, we consider the problem of making simultaneous decisions on the location, service rate (capacity) and the price of providing service for facilities on a network. We assume that the demand for service from each node of the network follows a Poisson process. The demand is assumed to depend on both price and distance. All facilities are assumed to charge the same price and customers wishing to obtain service choose a facility according to a Multinomial Logit function. Upon arrival to a facility, customers may join the system after observing the number of people in the queue. Service time at each facility is assumed to be exponentially distributed. We first present several structural results. Then, we propose an algorithm to obtain the optimal service rate and an approximate optimal price at each facility. We also develop a heuristic algorithm to find the locations of the facilities based on the tabu search method. We demonstrate the efficiency of the algorithms numerically.
机译:在本文中,我们考虑同时决定位置,服务速率(容量)和为网络上的设施提供服务的价格的问题。我们假设来自网络每个节点的服务需求遵循泊松过程。假定需求取决于价格和距离。假定所有设施都收取相同的价格,并且希望获得服务的客户会根据多项Logit函数选择设施。到达设施后,客户可以在观察队列中的人数之后加入系统。假定每个设施的服务时间呈指数分布。我们首先介绍几个结构结果。然后,我们提出一种算法,以获得每个设施的最优服务费率和近似最优价格。我们还开发了一种启发式算法,基于禁忌搜索方法来查找设施的位置。我们通过数值证明了算法的效率。

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