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The Vehicle Routing Problem (VRP) is a complex logistics and supply chain management challenge that involves optimizing routes for a fleet of vehicles to deliver goods to customers. Recent advancements in deep reinforcement learning (DRL) and metaheuristics offer promising solutions to enhance VRP efficiency and scalability. DRL combines reinforcement learning with deep neural networks to train agents to make optimal routing decisions. Metaheuristics, such as genetic algorithms and swarm intelligence, can also be used to effectively solve VRP.