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A pre-process clustering methods for the waste collection problem

机译:废物收集问题的预处理聚类方法

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Modern cities produce larger amounts of waste causing profound negative impacts on our natural environment. For this reason, processes related to waste collection, transportation, transformation and final disposal have increased their importance and major adequacy is desirable. Several Waste Management (WM) problems have to be solved in order to obtain efficient related services. Traditional Vehicle Routing Problem and Waste Collection Problem solution approaches presented in the literature are not suitable to face problems related to specific topology of the city, districts, street dimension and shape of the clusters. In this paper we propose a pre-process cluster solution in order to take into account different information such as street names, street dimension and civic number in order to create cluster more acceptable by the final users. In order to show the effectiveness of the proposed methodology, we compare hierarchical and spectral clustering-based algorithms. Finally, we apply our proposal in a real case study based on a data set extracted from a city in the north-east of Italy.
机译:现代城市产生大量废物,对我们的自然环境产生深远的负面影响。由于这个原因,与废物收集,运输,转化和最终处置有关的过程的重要性日益提高,并且需要有足够的充足性。为了获得有效的相关服务,必须解决几个废物管理(WM)问题。文献中提出的传统车辆路径问题和废物收集问题解决方法不适合面对与城市,地区,街道尺寸和集群形状有关的特定拓扑问题。在本文中,我们提出了一种预处理集群解决方案,以考虑到不同信息,例如街道名称,街道尺寸和公民编号,以创建最终用户更可接受的集群。为了显示所提出的方法的有效性,我们比较了基于分层和频谱聚类的算法。最后,我们基于从意大利东北部城市提取的数据集,在实际案例研究中应用了我们的建议。

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