生鲜产品零滞留与需求拆分下的生产配送优化算法OA

This study investigated the production and transportation scheduling problem with no on-site storage and job split-ting.A mixed-integer programming model was developed to minimize the total cost,which consists of backorder cost,inventory holding cost,and transportation cost,under constraints including sequence-dependent setup times and multiple hard time win-dows.To improve scalability on large instances,this paper proposed an enhanced heuristic algorithm.The upper level applied a dichotomy search.The lower level used a dual-population genetic algorithm and incorporated local search and simulated annea-ling to form a hybrid heuristic.Computational experiments demonstrate the practical value of both the model and the algorithm,with the optimized solution reducing the total cost by 8.17％.Further numerical results show that the improved heuristic achieves significantly better solution stability and quality while maintaining low computational complexity.Its Gap consistently remains be-low 3％,outperforming the dual-population genetic algorithm,the single-population genetic algorithm,and the Gurobi solver.