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

Oladimeji Samuel Sowole

International Journal of Mathematics in Operational Research, 2025, vol. 31, issue 1, 110-141

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.

Keywords: vehicle routing problem; VRP; search algorithms; metaheuristics; ant colony optimisation; ACO; particle swarm optimisation; PSO; genetic algorithms; GAs; Tabu search; simulated annealing; heuristics; routing strategies. (search for similar items in EconPapers)
Date: 2025
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