基于遗传算法的规则包装农产品三维装箱模型

    Genetic algorithm based three-dimension bin packing model for regular packaging agricultural products

    • 摘要: 随着农产品配送规模的扩大,物流成本不断增加,农产品的高效配送成为降低企业物流成本、增加企业竞争力的主要手段。该文针对农产品物流配送中多种货物的装箱问题,设计了一种基于遗传算法的智能三维装箱模型;通过分析农产品自身特点,在考虑装箱过程中车辆载质量、物品承重和体积等约束条件的基础上,对规则农产品的装箱次序以及摆放方向进行优化设计;应用Java技术对单车三维装箱算法进行了实现。采用北京郊区某公司的农产品货箱包装数据进行了10组试验测试,测试结果表明:用于综合描述装箱率和装箱成本的目标函数值平均为72.72%,采用遗传算法优化后,算法的平均运行时间为37 947 ms,目标函数值平均为81.14%,提高了8.42%。

       

      Abstract: With the development of agricultural products delivery, increasing the efficiency of the agri-food enterprises in distribution and reducing the logistics cost become more and more important. Therefore, in order to improve loading rate and loading cost, the three dimension bin packing problem (3BPP) for agricultural products was studied. With analyzing the features of agricultural products, considering the restrains of vehicle load, package size and bearing capacity, the putting sequence and directions of boxes were optimized by the GA algorithm for 3BPP. The algorithm was implemented by Java language which is an object oriented program language. Ten groups of experiments were carried out using the packing data acquired from an agricultural food production and distribution company, and the data were applied to test the algorithm. The results showed that the average running time was 37 947 ms, and the average value of objective function which can describe loading rate and loading cost was improved from 72.72% to 81.14%.

       

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