In this work, we present a real case application of a Rollon-Rolloff Vehicle Routing Problem (RRVRP) that arises at a waste collection company in Northern Italy. Compared to other RRVRP applications, where large containers are emptied and moved, our problem presents two additional types of services regarding the collection of bulk waste materials. Moreover, the problem deals with customer selection based on an objective function with two components: outsourcing costs incurred when customers are given to a third-party logistic operator, and internal routing costs. We model the RRVRP as a Mixed Integer Program and we solve it through a commercial solver and a simple but effective Iterated Greedy algorithm. Computational results are provided on 30 real case instances. Solutions provided by the Iterated Greedy are constantly better than the ones implemented by the company, showing that relevant cost reduction can be obtained with a limited computational effort.
Industrial Waste Collection Optimization: A Real-World Case Study in Northern Italy / Chiussi, A.; de Paula Felix, G.; Iori, M.; dos Santos, A. G.. - 13557 LNCS:(2022), pp. 147-161. (Intervento presentato al convegno International Conference on Computational Logistics tenutosi a Barcelona nel 21/09/2022) [10.1007/978-3-031-16579-5_11].
Industrial Waste Collection Optimization: A Real-World Case Study in Northern Italy
Chiussi A.;de Paula Felix G.;Iori M.;dos Santos A. G.
2022
Abstract
In this work, we present a real case application of a Rollon-Rolloff Vehicle Routing Problem (RRVRP) that arises at a waste collection company in Northern Italy. Compared to other RRVRP applications, where large containers are emptied and moved, our problem presents two additional types of services regarding the collection of bulk waste materials. Moreover, the problem deals with customer selection based on an objective function with two components: outsourcing costs incurred when customers are given to a third-party logistic operator, and internal routing costs. We model the RRVRP as a Mixed Integer Program and we solve it through a commercial solver and a simple but effective Iterated Greedy algorithm. Computational results are provided on 30 real case instances. Solutions provided by the Iterated Greedy are constantly better than the ones implemented by the company, showing that relevant cost reduction can be obtained with a limited computational effort.
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