Alweshah, M, Almiani, M, Almansour, N, Al Khalaileh, S, Aldabbas, H, Alomoush, W and Alshareef, A (2022) Vehicle routing problems based on Harris Hawks optimization. Journal of Big Data, 9 (1). ISSN 2196-1115
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Abstract
The vehicle routing problem (VRP) is one of the challenging problems in optimization and can be described as combinatorial optimization and NP-hard problem. Researchers have used many artificial intelligence techniques in order to try to solve this problem. Among these techniques, metaheuristic algorithms that can perform random search are the most promising because they can be used to find the right solution in the shortest possible time. Therefore, in this paper, the Harris hawks optimization (HHO) algorithm was used to attempt to solve the VRP. The algorithm was applied to 10 scenarios and the experimental results revealed that the HHO had a strong ability to check for and find the best route as compared to other metaheuristic algorithms, namely, simulated annealing and artificial bee colony optimization. The comparison was based on three criteria: minimum objective function obtained, minimum number of iterations required and satisfaction of capacity constraints. In all scenarios, the HHO showed clear superiority over the other methods.
Affiliation: | Skyline University College |
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SUC Author(s): | Alomoush, W ORCID: https://orcid.org/0000-0002-2937-4327 |
All Author(s): | Alweshah, M, Almiani, M, Almansour, N, Al Khalaileh, S, Aldabbas, H, Alomoush, W and Alshareef, A |
Item Type: | Article |
Uncontrolled Keywords: | Vehicle routing problem, Harris Hawks Optimization, Metaheuristic, Optimization |
Subjects: | B Information Technology > BM Artificial Intelligence |
Divisions: | Skyline University College > School of IT |
Depositing User: | Mr Veeramani Rasu |
Date Deposited: | 23 May 2022 16:41 |
Last Modified: | 23 May 2022 16:41 |
URI: | https://research.skylineuniversity.ac.ae/id/eprint/213 |
Publisher URL: | https://doi.org/10.1186/s40537-022-00593-4 |
Publisher OA policy: | https://v2.sherpa.ac.uk/id/publication/30870 |
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