Thangiah, Sam R., Salhi, Said (2001) Genetic Clustering: An Adaptive Heuristic for the Multi Depot Vehicle Routing Problem. Applied Artificial Intelligence, 15 (4). pp. 361-383. ISSN 0883-9514. (doi:10.1080/08839510151087293) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:5269)
| The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. | |
| Official URL: http://dx.doi.org/10.1080/08839510151087293 |
Abstract
A generalized clustering method based on a Genetic Algorithm is proposed. The Genetic Clustering (GenClust) method is used for solving the multidepot vehicle routing problem. The solution obtained by the genetic clustering method is improved using an efficient postoptimizer. A set of problems obtained from the literature are used to compare the efficiency of the genetic clustering method for solving the multidepot vehicle routing problem. The genetic clustering method found 11 new best known solutions from the 23 problems in the literature set.
| Item Type: | Article |
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| DOI/Identification number: | 10.1080/08839510151087293 |
| Subjects: | H Social Sciences |
| Divisions: | Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems |
| Depositing User: | Said Salhi |
| Date Deposited: | 17 Mar 2009 15:30 UTC |
| Last Modified: | 05 Nov 2024 09:37 UTC |
| Resource URI: | https://kar.kent.ac.uk/id/eprint/5269 (The current URI for this page, for reference purposes) |
University of Kent Author Information
Salhi, Said.
| Creator's ORCID: |
 https://orcid.org/0000-0002-3384-5240
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