A simheuristic algorithm for time-dependent waste collection management with stochastic travel times

A major operational task in city logistics is related to waste collection. Due to large problem sizes and numerous constraints, the optimization of real-life waste collection problems on a daily basis requires the use of metaheuristic solving frameworks to generate near-optimal collection routes in...

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Detalles Bibliográficos
Autores: Gruler, Aljoscha|||0000-0003-0510-117X, Pérez-Navarro, Antoni|||0000-0002-7037-0635, Calvet, Laura|||0000-0001-8425-1381, Juan, Ángel A.|||0000-0003-1392-1776
Tipo de recurso: artículo
Fecha de publicación:2020
País:España
Institución:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Idioma:inglés
OAI Identifier:oai:ddd.uab.cat:235235
Acceso en línea:https://ddd.uab.cat/record/235235
https://dx.doi.org/urn:doi:10.2436/20.8080.02.103
Access Level:acceso abierto
Palabra clave:Waste collection management
Vehicle routing problem
Stochastic optimization
Simheuristics
Biased randomization
Case study
Descripción
Sumario:A major operational task in city logistics is related to waste collection. Due to large problem sizes and numerous constraints, the optimization of real-life waste collection problems on a daily basis requires the use of metaheuristic solving frameworks to generate near-optimal collection routes in low computation times. This paper presents a simheuristic algorithm for the time-dependent waste collection problem with stochastic travel times. By combining Monte Carlo simulation with a biased randomized iterated local search metaheuristic, time-varying and stochastic travel speeds between different network nodes are accounted for. The algorithm is tested using real instances in a medium-sized city in Spain.