This research investigates an integrated inventory and production scheduling problem (IIPSP) in a manufacturer that deals with the perishable goods. The objective is to find an optimal schedule to minimize the sum of inventory cost and production cost. Both single-plant problem and multi-plant problem are investigated in this paper. For the single-plant problem, we prove that it is optimal to arrange the processing of raw materials in descending order of the value of the product of consumption rate and unit inventory cost. For the more complex multi-plant problem, we first prove that it is NP-hard, and then, we propose a hybrid intelligent algorithm to solve it. The experiments show that the proposed algorithm is superior to several other algorithms in both effectiveness and efficiency.

这项研究调查了处理易腐货物的制造商中的集成库存和生产计划问题（IIPSP）。目的是找到一个最佳计划，以最大程度地减少库存成本和生产成本之和。本文研究了单工厂问题和多工厂问题。对于单工厂问题，我们证明按原材料消耗率和单位库存成本的乘积值的降序安排原材料的加工是最佳的。对于更复杂的多工厂问题，我们首先证明它是NP难的，然后，提出了一种混合智能算法来解决它。实验表明，该算法在有效性和效率上均优于其他几种算法。