EURO 2024 Copenhagen
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792. A rolling horizon heuristic approach for a multi-stage stochastic waste collection problem

Invited abstract in session MA-35: Robust and Stochastic Routing Problems, stream Stochastic, Robust and Distributionally Robust Optimization.

Monday, 8:30-10:00
Room: 44 (building: 303A)

Authors (first author is the speaker)

1. Andrea Spinelli
Department of Management, Information and Production Engineering, University of Bergamo
2. Francesca Maggioni
Department of Management, Information and Production Engineering, University of Bergamo
3. Tania Ramos
IST-UL
4. Ana Barbosa-Povoa
Departamento de Engenharia e Gestão, Instituto Superior Técnico, Universidade de Lisboa
5. Daniele Vigo
DEI, University of Bologna

Abstract

We present a multi-stage stochastic optimization model for a waste collection routing problem. The problem is modeled as an inventory routing problem where decisions are related to the selection of bins to be visited and the corresponding visiting sequence in a predefined time horizon. The aim is the maximization of the total expected waste collection at lowest transportation cost, considering uncertainty in the waste accumulation rate in the network bins. Stochasticity in waste accumulation is modeled through scenario trees generated via conditional density estimation and dynamic stochastic approximation techniques. The model is solved through a rolling horizon approach, providing a worst-case analysis on its performance. Computational experiments are carried out on instances based on real data of a large Portuguese waste collection company. The impact of stochasticity on waste generation is examined through stochastic measures, and the performance of the rolling horizon approach is evaluated. Some managerial insights are finally discussed.

Keywords

Status: accepted

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