Vehicle Routing Problem

The Vehicle Routing Problem (VRP) focuses on optimizing delivery routes for fleets of vehicles to minimize costs while satisfying constraints like time windows and vehicle capacities. Current research emphasizes developing more generalizable and efficient solution methods, employing neural network architectures (including Transformers and graph attention networks) and algorithms like genetic algorithms, reinforcement learning, and hybrid approaches combining classical optimization with machine learning. These advancements aim to improve the efficiency and scalability of solutions for real-world logistics and transportation challenges, impacting fields like supply chain management and last-mile delivery. Furthermore, research is exploring fairness considerations and the application of quantum computing to tackle increasingly complex VRP variants.