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This research article presents a multi-objective vehicle routing optimization model aimed at improving the distribution of fresh products in Shenzhen, China, by minimizing costs related to freshness loss, cold-chain refrigeration, and delays while maximizing customer satisfaction. An improved genetic algorithm-based particle swarm optimization (MOGAPSO) is introduced to efficiently solve the routing problem under dynamic customer orders. A case study validates the model

Author

hossein hashemi

Language

EN