In the same-day delivery problem, requests with restricted time windows arrive during a given time horizon and it is necessary to decide which requests to serve and how to plan routes accordingly. We solve the problem with a dynamic stochastic method that invokes a generalized route generation function combined with an adaptive large neighborhood search heuristic. The heuristic is composed of destroying and repairing operators. The generalized route generation function takes advantage of sampled-scenarios, which are solved with the heuristic, to determine which decisions should be taken at any instant. Results obtained on different benchmark instances prove the effectiveness of the proposed method in comparison with a consensus function from the literature, with an average decrease of 10.7%, in terms of solution cost, and 24.5%, in terms of runtime.

Optimization Methods for the Same-Day Delivery Problem / Côté, Jean-François; de Queiroz, Thiago Alves; Gallesi, Francesco; Iori, Manuel. - 3:(2020), pp. 335-349. [10.1007/978-3-030-34960-8_30]

Optimization Methods for the Same-Day Delivery Problem

Gallesi, Francesco
Membro del Collaboration Group
;
Iori, Manuel
Membro del Collaboration Group
2020

Abstract

In the same-day delivery problem, requests with restricted time windows arrive during a given time horizon and it is necessary to decide which requests to serve and how to plan routes accordingly. We solve the problem with a dynamic stochastic method that invokes a generalized route generation function combined with an adaptive large neighborhood search heuristic. The heuristic is composed of destroying and repairing operators. The generalized route generation function takes advantage of sampled-scenarios, which are solved with the heuristic, to determine which decisions should be taken at any instant. Results obtained on different benchmark instances prove the effectiveness of the proposed method in comparison with a consensus function from the literature, with an average decrease of 10.7%, in terms of solution cost, and 24.5%, in terms of runtime.
26-gen-2020
Advances in Optimization and Decision Science for Society, Services and Enterprises
Paolucci M., Sciomachen A., Uberti P.
978-3-030-34959-2
978-3-030-34960-8
Springer, Cham
Optimization Methods for the Same-Day Delivery Problem / Côté, Jean-François; de Queiroz, Thiago Alves; Gallesi, Francesco; Iori, Manuel. - 3:(2020), pp. 335-349. [10.1007/978-3-030-34960-8_30]
Côté, Jean-François; de Queiroz, Thiago Alves; Gallesi, Francesco; Iori, Manuel
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1190448
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