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A pre-process clustering methods for the waste collection problem

机译:用于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:现代城市产生较大的废物,导致对我们的自然环境产生深远的负面影响。出于这个原因,与废物收集,运输,转型和最终处置有关的流程增加了重要性,可取的主要充分性是可取的。必须解决几种废物管理(WM)问题,以获得有效的相关服务。传统的车辆路由问题和废物收集问题文献中提出的方法不适合面对与城市,区,街道尺寸和集群形状的特定拓扑相关的问题。在本文中,我们提出了一个预处理群集解决方案,以考虑街道名称,街道维度和公民号码等不同信息,以创建最终用户更可接受的群集。为了展示所提出的方法的有效性,我们比较基于分层和光谱聚类的算法。最后,我们基于从意大利东北部提取的一个城市提取的数据集,在实际研究中应用我们的提案。

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