Abstract: This general fresh agricultural products logistics process can be divided into some independent units from the harvest to the sales. The energy consumption, quantity loss and quality level in the logistics process are clearly defined through the mathematical modeling. Then, taking the time and temperature of each logistics unit as the decision variables, taking the time limit and refrigeration conditions as the coupling constraints, and taking the minimum loss of energy consumption, quantity and quality as the optimization objective, the multi-objective cold chain logistics process optimization model of fresh agro-foods is established. The solution process based on non-dominated sorting genetic algorithm with elite strategy (NSGA-Ⅱ) is designed. An example of the optimization of Jointech companys cold meat logistics shows that under different constraint objectives, enterprises can obtain a variety of optimal time and temperature combination schemes for decision makers to choose. The multi-objective optimization solution results of cold and fresh meat can be divided into three categories, among which the slaughter time of cold and fresh meat has a greater impact on the loss cost and quality level of the whole logistics process, and more than half of the data obtained through simulation is affected by the slaughter time. With the improvement of the remaining quality level requirements, the impact of the temperature drop of each logistics unit on the loss cost is gradually reduced, especially when the remaining quality level requirements are above 86.4%, which is almost unaffected. At this time, under the established cost target, the company can improve the refrigeration conditions as much as possible to improve the quality level of cold fresh meat.

Key words: fresh agricultural products, cold chain logistics, logistics optimization, supply quality, Genetic algorithm

摘要： 生鲜农产品一般物流过程包括从采收到销售的若干独立的物流单元,通过模型抽象对物流过程中的能耗、数量损耗和质量水平进行清晰界定。以各物流单元的时间和温度为决策变量,以时限和制冷条件为耦合约束,以能耗、数量和质量的损耗最低为优化目标,建立生鲜农产品多目标冷链物流过程优化模型,并设计基于带精英策略的非支配排序的遗传算法(NSGA-Ⅱ)的求解过程。针对久通物联企业冷鲜肉物流过程的优化研究发现:在不同的约束目标下,企业可获得多种最优的时间温度组合方案供决策者选择;冷鲜肉多目标优化解集结果可分为3类,其中冷鲜肉宰杀时间对整个物流过程的损耗成本和质量水平有较大影响,在通过仿真获得的数据中有一半以上的数据受宰杀时间影响。随着剩余质量水平要求的提高,各物流单元温度下降对损耗成本的影响逐渐减小,尤其是剩余质量水平要求在86.4%以上时,几乎不受影响。此时在既定的成本目标下,企业可以尽可能提高制冷条件以提高冷鲜肉质量水平。

关键词: 生鲜农产品, 冷链物流, 物流优化, 供给质量, 遗传算法