We propose a bilevel optimization approach to tackle a hierarchical problem arising in Waste Management. The higher-level problem is interested in locating sorting facilities in a regional area, as well as defining the corresponding capacities. The lower-level problem defines an eective routing for servicing clients' pickup demand. The main idea behind the model is that the leader aims at finding the best location-allocation solution by clustering clients and by assigning facilities to these clusters without generating overlaps. In doing so, the leader tries to (i) assign clients' demand to facilities by considering a safety stock within their capacities, in order to avoid shortages during the operational phase, (ii) minimize Greenhouse Gases emissions, (iii) be as compliant as possible with the solution found by the lower-level problem, the latter aiming at balancing tour lengths performed by vehicles. After properly modeling the problem, we propose a metaheuristic solution algorithm, based on tabu search approach, and conduct an extensive computational analysis on a real-world scenario. Validation of the approach is achieved with promising results.
Clustering and Routing inWaste Management: A Bilevel Optimization Approach
Pinto DM;Stecca G
2022
Abstract
We propose a bilevel optimization approach to tackle a hierarchical problem arising in Waste Management. The higher-level problem is interested in locating sorting facilities in a regional area, as well as defining the corresponding capacities. The lower-level problem defines an eective routing for servicing clients' pickup demand. The main idea behind the model is that the leader aims at finding the best location-allocation solution by clustering clients and by assigning facilities to these clusters without generating overlaps. In doing so, the leader tries to (i) assign clients' demand to facilities by considering a safety stock within their capacities, in order to avoid shortages during the operational phase, (ii) minimize Greenhouse Gases emissions, (iii) be as compliant as possible with the solution found by the lower-level problem, the latter aiming at balancing tour lengths performed by vehicles. After properly modeling the problem, we propose a metaheuristic solution algorithm, based on tabu search approach, and conduct an extensive computational analysis on a real-world scenario. Validation of the approach is achieved with promising results.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.