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Improved ant colony optimisation for the dynamic multi-depot vehicle routing problem

Release Time:2019-03-10  Hits:

Indexed by: Journal Article

Date of Publication: 2013-04-01

Journal: INTERNATIONAL JOURNAL OF LOGISTICS-RESEARCH AND APPLICATIONS

Included Journals: Scopus、SSCI

Volume: 16

Issue: 2

Page Number: 144-157

ISSN: 1367-5567

Key Words: dynamic multi-depot vehicle routing problem; distance-based clustering approach; improved ant colony optimisation; nearest addition approach

Abstract: Dynamic vehicle routing problem (DVRP) with single depot has received increasing interest from engineers and scientists. Dynamic multi-depot vehicle routing problem (DMDVRP), an extension of DVRP, however, has not received much attention. In our paper, a distance-based clustering approach is introduced to simplify the DMDVRP by allocating each customer to its nearest depot. Thus, DMDVRP is decomposed to a sequence of DVRPs. An improved ant colony optimisation (IACO) with ant-weight strategy and mutation operation is presented to optimise vehicle routing problem (VRP) in this paper. Moreover, to satisfy the real-time feature of DMDVRP, the nearest addition approach is used to handle the new orders occurring during a time slice on the basis of VRP solution. Finally, the computational results for 17 benchmark problems are reported to validate that IACO with the distance-based clustering approach is more suitable for solving DMDVRP.

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