A solution methodology for a Smart Waste Collection Routing Problem with workload concerns: computational and managerial insights from a real case study

Carolina Soares de Morais, Diana Rita Ramos Jorge, Ana Raquel Aguiar, Ana Paula Barbosa-Póvoa, António Pais Antunes, Tânia Rodrigues Pereira Ramos

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

The focus of this paper is the Smart Waste Collection Routing Problem (SWCRP) with workload concerns, a variant of the well-known Vehicle Routing Problem (VRP). Specifically, we propose a solution methodology to address medium to large size problems consisting of two phases. In the first phase, a look-ahead heuristic is used to decide when to perform collection routes considering that real-time information is available through sensors located inside the waste bins. In the second phase, it defines the routes to perform using either an optimisation-based approach or a hybrid metaheuristic approach. A large-size real case study is used to test these approaches. Significant improvements on the key performance indicators characterising the waste collection operations demonstrate the benefits that can be achieved through the proposed solution methodology, within balanced collection routing plans are designed. Moreover, computational and managerial insights about adding workload concerns and performing multi-municipality versus single-municipality operations are provided for the case study.

Original languageEnglish
Article number2086717
JournalInternational Journal of Systems Science: Operations and Logistics
Volume10
Issue number1
DOIs
Publication statusPublished - 2023

Bibliographical note

Publisher Copyright:
© 2022 Informa UK Limited, trading as Taylor & Francis Group.

Funding

This research was financially supported by the ‘Fundação para a Ciência e Tecnologia’ (FCT - Portugal) under the research project MIT-EXPL/SUS/0132/2017, and project UIDB/00097/2020 (CEGIST).

FundersFunder number
CEGIST
Fundação para a Ciência e a TecnologiaUIDB/00097/2020, MIT-EXPL/SUS/0132/2017

    Keywords

    • Routing
    • hybrid metaheuristic
    • optimisation-based approach
    • smart waste collection
    • workload concerns

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