Exploring the Capacitated Vehicle Routing Problem using the power of Machine Learning : A Literature Review

The Capacitated Vehicle Routing Problem is a classic logistics
optimization challenge for which numerous approaches are employed to address it. A prevalent strategy involves employing machine learning for predicting demand, leveraging historical data to accurately forecast customer needs. Furthermore, reinforcement learning techniques are employed to optimize vehicle routes, adapting them dynamically in response to changing traffic conditions and new customer requests. Hybrid models combining traditional optimization algorithms with machine learning have shown promise in improving the quality of solutions. Dive into this state-of-the-art compilation, we have meticulously gathered and synthesized related studies to provide a thorough overview and deliver readers an insightful comprehension of the latest statement of the CVRP.