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Accelerated hyperbolic smoothing method for solving the multisource Fermat-Weber and k-Median problems

机译:解决多源Fermat-Weber和k-Median问题的加速双曲平滑方法

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摘要

This article deals with the Multisource Fermat-Weber and continuous k-Median problems. The first problem is the continuous location-allocation problem, defined in a planar region, an important problem in facility location subject. The continuous k-Median problem, defined in a multidimensional space, is also known as the minimum sum-of-distances clustering problem. Their mathematical modellings lead to a min-sum-min formulation which is a global optimization problem with a bilevel nature, nondifferentiable and with many minimizers. To overcome these severe difficulties, the Hyperbolic Smoothing methodology is proposed, in connection with a partition of locations in two groups: location in the frontier and location in gravitational regions, which drastically simplify the computational tasks. For the purpose of illustrating both the reliability and the efficiency of the method, we perform a set of computational experiments making use of the traditional instances described in the literature. Apart from consistently presenting similar or even better results when compared to related approaches, the novel technique was able to deal with instances never tackled before, with up to 1243088 cities. (C) 2019 Elsevier B.V. All rights reserved.
机译:本文讨论了多源Fermat-Weber和连续k-Median问题。第一个问题是在平面区域中定义的连续位置分配问题,这是设施定位主题中的重要问题。在多维空间中定义的连续k中值问题也称为最小距离总和聚类问题。他们的数学模型导致了最小和最小的公式化,这是一个全局优化问题,具有双层性质,不可微且具有许多最小化因素。为了克服这些严峻的困难,提出了双曲线平滑方法,将位置分为两组:边界位置和重力区域,这大大简化了计算任务。为了说明该方法的可靠性和效率,我们利用文献中描述的传统实例进行了一组计算实验。与相关方法相比,除了持续呈现相似甚至更好的结果外,该新技术还能够处理多达1243088个城市以前从未处理过的实例。 (C)2019 Elsevier B.V.保留所有权利。

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