TY - JOUR
T1 - A solution methodology for a Smart Waste Collection Routing Problem with workload concerns
T2 - computational and managerial insights from a real case study
AU - de Morais, Carolina Soares
AU - Ramos Jorge, Diana Rita
AU - Aguiar, Ana Raquel
AU - Barbosa-Póvoa, Ana Paula
AU - Antunes, António Pais
AU - Ramos, Tânia Rodrigues Pereira
N1 - Publisher Copyright:
© 2022 Informa UK Limited, trading as Taylor & Francis Group.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - Routing
KW - hybrid metaheuristic
KW - optimisation-based approach
KW - smart waste collection
KW - workload concerns
UR - http://www.scopus.com/inward/record.url?scp=85132138192&partnerID=8YFLogxK
U2 - 10.1080/23302674.2022.2086717
DO - 10.1080/23302674.2022.2086717
M3 - Article
AN - SCOPUS:85132138192
SN - 2330-2674
VL - 10
JO - International Journal of Systems Science: Operations and Logistics
JF - International Journal of Systems Science: Operations and Logistics
IS - 1
M1 - 2086717
ER -