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How Does Different Algorithm Work When Applied on the Different Road Networks When Optimal Location of Facilities Is Searched for in Rural Areas?

机译:当在农村地区搜索设施的最佳位置时,如何在不同的道路网络上应用不同的算法?

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The p-median problem is often used to locate P service facilities in a geographically distributed population. Important for the performance of such a model is the distance measure. The first aim in this study is to analyze how the optimal location solutions vary, using the p-median model, when the road network is alternated. It is hard to find an exact optimal solution for p-median problems. Therefore, in this study two heuristic solutions are applied, simulating annealing and a classic heuristic. The secondary aim is to compare the optimal location solutions using different algorithms for large p-median problem. The investigation is conducted by the means of a case study in a rural region with a. asymmetrically distributed population, Dalecarlia. The study shows that the use of more accurate road networks gives better solutions for optimal location, regardless what algorithm that is used and regardless how many service facilities that is opt for. It is also shown that the Simulating annealing algorithm not just is much faster than the classic heuristic used here, but also in most cases gives better solutions.
机译:P-Median问题通常用于在地理上分布的人口中定位P服务设施。对于这种模型的性能很重要,是距离测量。本研究中的第一个目的是分析最佳位置解决方案如何使用P-Median模型来改变,当交替的道路网络时。很难找到对P-Median问题的精确最佳解决方案。因此,在本研究中,应用了两个启发式解决方案,模拟退火和经典的启发式。二次目的是使用不同算法进行比较最佳位置解决方案以进行大型正值问题。调查是通过案例研究的案例研究,其中一个案例研究。不对称分布的人口,Dalecarlia。该研究表明,使用更准确的道路网络提供更好的最佳位置的解决方案,无论使用哪些算法,无论选择多少个服务设施。还表明,模拟退火算法不仅比这里使用的经典启发式更快,而且在大多数情况下也提供了更好的解决方案。

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