Vehicle routing problems based on Harris Hawks optimization

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 algo...

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Bibliographic Details
Published in:Journal of big data 2022-04, Vol.9 (1), p.1-18, Article 42
Main Authors: Alweshah, Mohammed, Almiani, Muder, Almansour, Nedaa, Al Khalaileh, Saleh, Aldabbas, Hamza, Alomoush, Waleed, Alshareef, Almahdi
Format: Article
Language:English
Subjects:
Algorithms
Artificial intelligence
Big Data
Combinatorial analysis
Communications Engineering
Computational Science and Engineering
Computer Science
Data Mining and Knowledge Discovery
Database Management
Harris Hawks Optimization
Heuristic methods
Information Storage and Retrieval
Mathematical Applications in Computer Science
Metaheuristic
Networks
Optimization
Route planning
Simulated annealing
Swarm intelligence
Vehicle routing
Vehicle routing problem
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Summary: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.
ISSN:2196-1115
2196-1115
DOI:10.1186/s40537-022-00593-4