A pre-process clustering methods for the waste collection problem

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.