Tobler’s Law and Spatial Optimization
Tobler’s Law and Spatial Optimization
复制标题
托布勒定律和空间优化
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
R. Church
中科院分区：
文献类型：
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作者：
R. Church
1970年，托布勒制作了一部模拟底特律市人口增长的电影。他辩称，他的模型不需要包括新加坡等遥远地方的术语，但通过引用他所说的地理第一定律，他的预测仍然相对准确。在空间优化中，像一般的仓库选址问题(GWLP)一样，假设需要包括所有可能的联系，因为任意丢弃潜在变量可能会阻止确定最优解。在这篇文章中，它证明了有可能达到这样严格的标准，在空间优化，同时指导托布勒的论点是简单和节俭。本文以GWLP为例演示了如何实现这一点。提出了一种新的模型形式，该模型区分了“近”(低成本)分配和“远”(高成本)分配，并同时使用显式和隐式变量进行能力分配。给出了使用该模型的计算经验，结果表明，在消除大量分配/运输变量和约束的同时，可以识别和验证最优解。本文最后对区域科学中其他空间优化问题的重新表述和再发展提出了挑战。
In 1970, Tobler produced a movie simulating population growth in the City of Detroit. He argued that his model did not need to include terms for faraway places like Singapore, while still being relative accurate in his forecast by invoking what he called the first law of geography. In spatial optimization, like the general warehouse location problem (GWLP), it is assumed that all possible linkages need to be included, as arbitrarily dropping potential variables may prevent optimal solutions from being identified. In this article, it is demonstrated that it may be possible to meet such exacting standards in spatial optimization, while at the same time being guided by Tobler’s argument for being simple and frugal. This article gives a demonstration of how this might be achieved using the GWLP as an example. A new model form is proposed which distinguishes between “near” (low cost) allocations and “far” (high cost) allocations and uses both explicit and implicit variables for capacity allocations. Computational experience in using this new model is given which shows that optimal solutions can be identified and verified while eliminating a substantial number of allocation/transport variables and constraints. This article ends with a challenge for the reformulation and redevelopment of other spatial optimization problems in regional science.