The Vehicle Routing Problem (VRP) is one of the basic combinatorial optimization problems that takes a central place in the sphere of logistics, transportation, and supply-chain management. A systematic literature review (SLR) of VRP scholarship dated 2000 to 2025 is conducted herein, where over 500,000 publications are analyzed to carry out the study of VRP solutions evolution and methodological advancements as well as their practical use. The results highlight the current popularity of metaheuristic algorithms, such as Ant Colony Optimization (ACO), Genetic Algorithms (GA), and Particle Swarm Optimization (PSO), in solving complex variants of VRP, in particular, the Capacitated Vehicle Routing Problem (CVRP) and the Vehicle Routing Problem with Time Windows (VRPTW). The combination of real-time data streams, machine-learning methods and adaptive algorithms represents a revolutionary track, and helps to develop more active and responsive VRP models. Moreover, increased attention to sustainability and green logistics has triggered the development of the eco-efficient VRP models, which combine the use of electric vehicles (EVs) and energy-consumption optimization. The spread of autonomous vehicles presents new opportunities and threats to future VRP solutions, particularly in the area of urban freight and last-mile delivery. In conclusion, the review outlines future streams of research, highlighting the need to find adaptive, sustainable, and autonomous VRP models that can resolve the growing complexities in the modern world of logistics.
Pangaribuan et al. (Mon,) studied this question.