Solving the vehicle routing problem with search algorithms: a comparative analysis

The vehicle routing problem (VRP) is a well-known optimisation problem in operations research, with applications in logistics, transportation, and supply chain management. This paper offers a comparative analysis of search algorithms used to solve the VRP, focusing on their strengths and weaknesses. It introduces the VRP and its variants, highlighting the challenges and constraints involved. Various search algorithms, such as genetic algorithms, simulated annealing, and ant colony optimisation, are examined, discussing their principles, advantages, and limitations. Real-world case studies in package delivery, waste collection, and emergency response demonstrate the application of these algorithms. Factors influencing algorithm performance, including problem size, complexity, and parameters, are discussed. Recommendations for selecting appropriate search algorithms for different VRP instances are provided. The paper aims to provide readers with a comprehensive understanding of using search algorithms to solve the VRP, aiding decision-making in similar optimisation problems.

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Publication Details

Journal
International Journal of Mathematics in Operational Research
Published
2025-01-01
DOI
https://doi.org/10.1504/ijmor.2025.146360
Primary Topic
Vehicle Routing Optimization Methods
Type
article
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article

Solving the vehicle routing problem with search algorithms: a comparative analysis

Oladimeji Samuel Sowole
International Journal of Mathematics in Operational Research
Vehicle Routing Optimization Methods
article

Solving the vehicle routing problem with search algorithms: a comparative analysis

Oladimeji Samuel Sowole
article en

Abstract

The vehicle routing problem (VRP) is a well-known optimisation problem in operations research, with applications in logistics, transportation, and supply chain management. This paper offers a comparative analysis of search algorithms used to solve the VRP, focusing on their strengths and weaknesses. It introduces the VRP and its variants, highlighting the challenges and constraints involved. Various search algorithms, such as genetic algorithms, simulated annealing, and ant colony optimisation, are examined, discussing their principles, advantages, and limitations. Real-world case studies in package delivery, waste collection, and emergency response demonstrate the application of these algorithms. Factors influencing algorithm performance, including problem size, complexity, and parameters, are discussed. Recommendations for selecting appropriate search algorithms for different VRP instances are provided. The paper aims to provide readers with a comprehensive understanding of using search algorithms to solve the VRP, aiding decision-making in similar optimisation problems.

International Journal of Mathematics in Operational ResearchVol. 31(1)
African Institute for Mathematical Sciences (ZA)
Openalex Percentile: Top 84%
Vehicle Routing Optimization Methods
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