Resumen

PATINO CHIRVA, Johana Andrea; DAZA CRUZ, Yesica Xiomara  y  LOPEZ-SANTANA, Eduyn Ramiro. A Hybrid Mixed-Integer Optimization and Clustering Approach to Selective Collection Services Problem of Domestic SolidWaste. ing. [online]. 2016, vol.21, n.2, pp.235-257. ISSN 0121-750X.  https://doi.org/10.14483/udistrital.jour.reving.2016.2.a09.

Context: Waste generation is causing profound negative impacts on our natural environment. Because of that, processes related to waste collection, transportation, transformation and final disposal have increased its importance and major efficiencies are is desirable. We propose a Mixed Integer Programming model and clustering approach for waste collection and transportation process. Method: An optimization model, inspired on Bogotá context is proposed, to maximize the amount of waste collected, considering real-life aspects of this activity in the city. For large instances in which there is a big computational cost, we proposed an alternative solution of two stages, firstly a clustering step and then a routing step. Results: In small instances of up to 1453 collection sites grouped in 13 blocks and 51 corners, the model result in an overall collection covering of 100%. For large instances, there are variations between the results of each clustering method. The results suggests that the sweep algorithm is better to clustering the collection sites. Conclusions: Our proposed model is able to find a solution the waste collection problem in Bogota case considering the vehicle capacity, maximum workday duration and the planning horizon of two days according with the collection process in Bogota. We test three clustering methods in order to group the collection sites and to reduce the complexity of the problem, and then we solve the model using a commercial solver. For the small instances, our model run very fast but in the large in-stances the computational time was increased. Future work will focus in the validation and search of solution methods improving the performance with the proposed model.

Palabras clave : clustering; optimization model; routing; scheduling; waste collection services.

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