Optimization of the vehicle routing problem for solid waste management

The issue of optimizing vehicle routing for solid waste recovery presents a significant economic and ecological challenge for society. Indeed, the vehicle routing problem (VRP) is part of the best-known combinatorial optimization problems, it consists of searching for the best itineraries for a group of vehicles leaving a depot for the purpose of visit a cluster of customers by meeting a group of limitations such as total transport cost, vehicle capacity and delivery times. This problem is a classic extension of the traveling salesman problem, it is a part of the class of NP-difficult optimization problems. The different types of algorithms and methods that exist to solve this problem mainly distinguish three types of methods: classical approaches based on mathematical programming, heuristic approaches and approaches based on machine learning. Although VRP is classified as an NP-hard problem, various approaches have been established to solve this problem accurately. Recent advancements in the disciplines of artificial intelligence and combinatorial optimization offer new perspectives to improve VRP resolution more efficiently. Therefore, this work will present the state of the art of vehicle routing problem, we will establish a bibliometric analysis on this theme in order to review and synthesize the literature related to the VRP.