A Heuristic Algorithm for the Capacitated Multiple Supplier Inventory Grouping Problem
针对多供应商库存分组问题，提出一种结合次梯度优化和原始启发式的算法，快速求解物流成本最小化模型，经测试比商用整数规划代码更高效。
This paper presents and solves a model for the multiple supplier inventory grouping problem, which involves the minimization of logistics costs for a firm that has multiple suppliers with capacity limitations. The costs included in the model are purchasing, transportation, ordering, and inventory holding, while the firm's objective is to determine the optimal flows and groups of commodities from each supplier. We present an algorithm, which combines subgradient optimization and a primal heuristic, to quickly solve the multiple supplier inventory grouping problem. Our algorithm is tested extensively on problems of various sizes and structures, and its performance is compared to that of OSL, a state‐of‐the‐art integer programming code. The computational results indicate that our approach is extremely efficient for solving the multiple supplier inventory grouping problem.