基于批次关联的鲜切蔬菜采购成本-召回规模联合优化

Joint Optimization of Purchasing Cost-Recall Scale Model of Fresh-cut Vegetables Based on Batch Association

鲜切蔬菜从采购、加工到包装存在批次混合,批次混合程度和采购成本相互制约,因此提出一种建立原材料与订单产品批次关联的采购-召回方案。根据鲜切加工企业的生产计划和加工流程,满足订单要求和供应商的原材料条件,建立批次混合程度和采购成本为目标函数的混合整形线性规划(Mixed-integer linear programing,MILP)模型。使用LINGO对模型逐步求解,结果显示,随着批次混合程度的增加原材料的采购成本逐渐降低,当批次混合程度为10时,采购成本最低为2 840.33元,平均召回数量177.50 kg,适用于中小型鲜切加工企业。

The batch mixing exists for fresh-cut vegetables from purchasing,processing to packaging,and there is mutual restrictive relationship between batch mixing degree and purchasing cost. The singleobjective model cannot meet the requirement of flexible production. Therefore,a kind of purchasing costrecall model was proposed to build batch relations between raw material and order products. According to production plan and process flow of fresh-cut processing enterprise,taking the batch mixing degree and the purchasing cost as objective functions,a mixed-integer linear programming model was established to meet the order requirements and the suppliers＇ raw material conditions. Since the weight of recall number was more important than that of procurement costs,and high correspondence relationship existed between recall number and batch mixing degree,the hierarchical sequence method was used to solve the multiobject model. The established model was analyzed by the LINGO software in the step-by-step solution process. The model performance was evaluated with parameters,such as purchase cost,average number of recall and the maximum number of recall. The results showed that with the increase of batch mixing degree,the procurement costs of raw materials were reduced gradually. When batch mixing degree was10,the lowest cost of purchase was 2 840. 33 yuan,the average recall quantity was 177. 50 kg,and the maximum recall quantity was 420 kg. In order to evaluate the practical applicability of the model,the average recall ratio and maximum recall ratio were introduced. The results showed that when batch mixing degree was 10,the average recall ratio and maximum recall ratio were 15. 5% and 36. 8%,respectively,which were suitable for medium and small fresh-cut processing enterprises.