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Efficient neighborhood evaluations for the vehicle routing problem with multiple time windows

Efficient neighborhood evaluations for the vehicle routing problem with multiple time windows
Efficient neighborhood evaluations for the vehicle routing problem with multiple time windows

In the vehicle routing problem with multiple time windows (VRPMTW), a single time window must be selected for each customer from the multiple time windows provided. Compared with classical vehicle routing problems with only a single time window per customer, multiple time windows increase the complexity of the routing problem. To minimize the duration of any given route, we present an exact polynomial time algorithm to efficiently determine the optimal start time for servicing each customer. The proposed algorithm has a reduced worst-case and average complexity than existing exact algorithms. Furthermore, the proposed exact algorithm can be used to efficiently evaluate neighborhood operations during a local search resulting in significant acceleration. To examine the benefits of exact neighborhood evaluations and to solve the VRPMTW, the proposed algorithm is embedded in a simple metaheuristic framework generating numerous new best known solutions at competitive computation times.

0041-1655
299-564
Hoogeboom, Maaike
50730fb2-0e78-4cb7-bf39-6e8ce4bfc73e
Dullaert, Wout
315bc5f3-4982-42d7-a659-2bf8e910b7ba
Lai, David S.W.
9e095afb-da7c-42e3-9e3e-a609bf12da57
Vigo, Daniele
18bccf8b-3312-4105-8da2-db60e3924712
Hoogeboom, Maaike
50730fb2-0e78-4cb7-bf39-6e8ce4bfc73e
Dullaert, Wout
315bc5f3-4982-42d7-a659-2bf8e910b7ba
Lai, David S.W.
9e095afb-da7c-42e3-9e3e-a609bf12da57
Vigo, Daniele
18bccf8b-3312-4105-8da2-db60e3924712

Hoogeboom, Maaike, Dullaert, Wout, Lai, David S.W. and Vigo, Daniele (2020) Efficient neighborhood evaluations for the vehicle routing problem with multiple time windows. Transportation Science, 54 (2), 299-564, [C2]. (doi:10.1287/trsc.2019.0912).

Record type: Article

Abstract

In the vehicle routing problem with multiple time windows (VRPMTW), a single time window must be selected for each customer from the multiple time windows provided. Compared with classical vehicle routing problems with only a single time window per customer, multiple time windows increase the complexity of the routing problem. To minimize the duration of any given route, we present an exact polynomial time algorithm to efficiently determine the optimal start time for servicing each customer. The proposed algorithm has a reduced worst-case and average complexity than existing exact algorithms. Furthermore, the proposed exact algorithm can be used to efficiently evaluate neighborhood operations during a local search resulting in significant acceleration. To examine the benefits of exact neighborhood evaluations and to solve the VRPMTW, the proposed algorithm is embedded in a simple metaheuristic framework generating numerous new best known solutions at competitive computation times.

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More information

Accepted/In Press date: 6 January 2020
e-pub ahead of print date: 6 January 2020
Published date: 1 March 2020

Identifiers

Local EPrints ID: 457648
URI: http://eprints.soton.ac.uk/id/eprint/457648
ISSN: 0041-1655
PURE UUID: a5b8af9f-8e62-452f-b593-831a7796f6ba
ORCID for David S.W. Lai: ORCID iD orcid.org/0000-0002-9989-1485

Catalogue record

Date deposited: 14 Jun 2022 16:56
Last modified: 15 Jun 2022 01:59

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Contributors

Author: Maaike Hoogeboom
Author: Wout Dullaert
Author: David S.W. Lai ORCID iD
Author: Daniele Vigo

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