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The Weber obnoxious facility location model: A Big Arc Small Arc approach

机译:韦伯令人讨厌的设施选址模型:大弧小弧方法

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In this paper we propose the Weber obnoxious facility location problem. As in the classic Weber location problem, the objective is to minimize the weighted sum of distances between the facility and demand points. However, the facility location is required to be at least a given distance from demand points because it is "obnoxious" to them. A practical example is locating an airport. Since in most applications the nuisance generated by the facility "travels by air", we concentrate on the case where the required minimum distance between the facility and demand points is Euclidean. The Weber objective distance can be measured by a different norm. We develop very efficient algorithms to optimally solve the single facility problem based on geometric branch and bound and on a finite candidate set. We tested it on problems with up to 10,000 demand points using Euclidean, Manhattan, and l(p) for p = 1.78 norms for the Weber objective. The largest problems were optimally solved in a few seconds of computer time. Many extensions to the basic Weber obnoxious facility location problem are proposed for future research. (C) 2018 Published by Elsevier Ltd.
机译:在本文中,我们提出了韦伯令人讨厌的设施选址问题。像经典的韦伯定位问题一样,目标是使设施和需求点之间的距离的加权总和最小化。但是,设施位置必须与需求点至少相距给定距离,因为它对需求点“有害”。一个实际的例子是找到机场。由于在大多数应用中,设施产生的滋扰是“空中旅行”,因此我们将重点放在设施与需求点之间所需的最小距离为欧几里得的情况。韦伯物镜距离可以用不同的范数来衡量。我们开发了非常有效的算法,可以基于几何分支和边界以及有限的候选集来最佳地解决单设施问题。我们使用Euclidean,Manhattan和l(p)检验了高达10,000个需求点的问题,其中Weber目标的p = 1.78范数。最大的问题可以在几秒钟的计算机时间内得到最佳解决。提出了对基本Weber讨厌设施位置问题的许多扩展,以供将来研究之用。 (C)2018由Elsevier Ltd.发布

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  • 来源
    《Computers & operations research》 |2018年第10期|240-250|共11页
  • 作者单位

    Calif State Univ Fullerton, Steven G Mihaylo Coll Business & Econ, Fullerton, CA 92834 USA;

    Calif State Univ Fullerton, Steven G Mihaylo Coll Business & Econ, Fullerton, CA 92834 USA;

    Georg August Univ Gottingen, Inst Numer & Angew Math, Gottingen, Germany;

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