Modeling and solving the non-smooth arc routing problem with realistic soft constraints

This paper considers the non-smooth arc routing problem (NS-ARP) with soft constraints in order to capture in more perceptive way realistic constraints violations arising in transportation and logistics. To appropriately solve this problem, a biased-randomized procedure with iterated local search (B...

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Detalles Bibliográficos
Autores: De Armas, Jésica, Ferrer, Albert, Juan, Angel A., Lalla-Ruiz, Eduardo
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2018
País:España
Institución:Universitat Pompeu Fabra
Repositorio:Repositorio Digital de la UPF
OAI Identifier:oai:repositori.upf.edu:10230/59079
Acceso en línea:http://hdl.handle.net/10230/59079
http://dx.doi.org/10.1016/j.eswa.2018.01.020
Access Level:acceso abierto
Palabra clave:Arc routing problem
Soft constraints
Non-smooth optimization
Biased-randomization
Metaheuristics
Descripción
Sumario:This paper considers the non-smooth arc routing problem (NS-ARP) with soft constraints in order to capture in more perceptive way realistic constraints violations arising in transportation and logistics. To appropriately solve this problem, a biased-randomized procedure with iterated local search (BRILS) and a mathematical model for this ARP variant is proposed. An extensive computational study is conducted on rich and diverse problem instances. The results highlight the competitiveness of BRILS in terms of quality and time, where it provides high-quality solutions within reasonable computational times. In the context of real-world environments, the performance exhibited by BRILS motivates its incorporation in intelligent and integrative systems where frequent and fast solutions are required.