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基于批次關(guān)聯(lián)的鮮切蔬菜采購(gòu)成本-召回規(guī)模聯(lián)合優(yōu)化
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“十二五”國(guó)家科技支撐計(jì)劃項(xiàng)目(2013BAD19B04)


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

    鮮切蔬菜從采購(gòu),、加工到包裝存在批次混合,批次混合程度和采購(gòu)成本相互制約,,因此提出一種建立原材料與訂單產(chǎn)品批次關(guān)聯(lián)的采購(gòu)-召回方案,。根據(jù)鮮切加工企業(yè)的生產(chǎn)計(jì)劃和加工流程,滿足訂單要求和供應(yīng)商的原材料條件,,建立批次混合程度和采購(gòu)成本為目標(biāo)函數(shù)的混合整形線性規(guī)劃(Mixed-integer linear programing, MILP)模型,。使用LINGO對(duì)模型逐步求解,結(jié)果顯示,,隨著批次混合程度的增加原材料的采購(gòu)成本逐漸降低,,當(dāng)批次混合程度為10時(shí),采購(gòu)成本最低為2 840.33元,,平均召回?cái)?shù)量177.50 kg,,適用于中小型鮮切加工企業(yè)。

    Abstract:

    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 single- objective model cannot meet the requirement of flexible production. Therefore, a kind of purchasing cost- recall 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 multi-object 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 was 10, 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.

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楊信廷,王健,錢建平,邢斌,曹文琴,王貴用.基于批次關(guān)聯(lián)的鮮切蔬菜采購(gòu)成本-召回規(guī)模聯(lián)合優(yōu)化[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2016,47(2):222-227. Yang Xinting, Wang Jian, Qian Jianping, Xing Bin, Cao Wenqin, Wang Guiyong. Joint Optimization of Purchasing Cost Recall Scale Model of Fresh-cut Vegetables Based on Batch Association[J]. Transactions of the Chinese Society for Agricultural Machinery,2016,47(2):222-227.

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  • 收稿日期:2015-09-06
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  • 在線發(fā)布日期: 2016-02-25
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