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研究了钢铁工业从原料采购到初级产品生产的物流计划问题,包括运输、库存和面向生产的配送.以所考虑的相关成本最小化为目标建立了数学规划模型,并采用列生成的方法求解.对0-1变量的线性松弛采用启发式的分支和深度优先搜索策略尽可能快地获得好的可行解.在分支结点上,通过求解最短路子问题获得限制主问题所需要的列,分支树上的根结点提供了体现可行解质量的下界.最后,计算机随机试验验证了该模型的有效性和算法的稳定.
The logistics planning of the steel industry from raw material procurement to primary product production was studied, including transportation, inventory and production-oriented delivery.Mathematical planning models were established with the objective of minimizing the relevant costs under consideration and solved by the method of column generation. For the linear relaxation of the 0-1 variable, heuristic branches and depth-first search strategies are used to get a good feasible solution as fast as possible.On the branch nodes, we obtain the necessary columns to limit the main problem by solving the shortest-path sub-problem, The root node provides a lower bound that reflects the quality of the feasible solution.Finally, a computer randomized test verifies the effectiveness of the model and the stability of the algorithm.