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首页> 外文期刊>Journal of Computational and Applied Mathematics >Exact and heuristic solutions of a discrete competitive location model with Pareto-Huff customer choice rule
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Exact and heuristic solutions of a discrete competitive location model with Pareto-Huff customer choice rule

机译:帕拉夫客户选择规则的离散竞争位置模型的精确和启发式解决方案

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摘要

An entering firm wants to compete for market share of an area by opening some new facilities selected among a finite set of potential locations (discrete space). Customers are spatially separated and there already are other firms operating in that area. In this paper, we use a variant of the well known Huff (proportional) customer choice rule, the so called Pareto-Huff, which have had little attention on the literature because of its nonlinear formulation. This untested rule considers that customers split their demand among the facilities that are Pareto optimal with respect to quality (to be maximized) and distance (to be minimized), proportionally to their attractions, i.e., a distant facility will capture demand of a customer only if it has higher quality than any other closer facility. A first formulation as a nonlinear programming problem is proposed, and then an equivalent formulation as a linear programming problem is presented, which allows us to obtain exact solutions for medium size problems. For large size problems, a heuristic procedure is also proposed to obtain the best approximate solutions. Its performance is checked for small size problems and its solutions are compared with the optimal solutions given by a standard optimizer, Xpress, using real geographical coordinates and population data of municipalities in Spain. (C) 2020 Elsevier B.V. All rights reserved.
机译:进入的公司希望通过在有限的潜在地点(离散空间)中选择一些新设施来竞争某一地区的市场份额。客户在空间上是分离的,而且已经有其他公司在该地区运营。在本文中,我们使用了著名的赫夫(比例)客户选择规则的一种变体,即所谓的帕累托-赫夫规则,由于其非线性公式,该规则很少受到文献的关注。这一未经测试的规则认为,客户将他们的需求在质量(要最大化)和距离(要最小化)方面的帕累托最优设施中进行分配,这与他们的吸引力成比例,即,只有当一个较远的设施的质量高于任何其他较近的设施时,它才会捕获客户的需求。首先提出了一个非线性规划问题的形式,然后给出了一个线性规划问题的等价形式,这使我们能够获得中等规模问题的精确解。对于大型问题,还提出了一种启发式方法来获得最佳近似解。针对小规模问题检查其性能,并将其解决方案与标准优化器Xpress给出的最佳解决方案进行比较,该优化器使用西班牙各市的真实地理坐标和人口数据。(C) 2020爱思唯尔B.V.版权所有。

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