基于增强蜂群算法的农产品多目标供应链优化

发布时间：2018-06-02 09:27

本文选题：蜂群算法 + 农产品基地　；参考：《控制工程》2016年07期

【摘要】：农产品的生产与供应对成本与供货时间要求极高,提出一种增强的蜂群算法来优化农产品基地的多基地、多目标供应链优化问题。首先,将蜂群中适应度值最高的地点选为目标地点,将其作为邻域搜索的输入参数,并为目标地点分配较多的搜索蜂,为非目标地点分配较少的搜索蜂;然后,经过一定次数的迭代搜索后,放弃其中改进不明显的地点,以此避免陷入局部最优并提高收敛速度;最终,将增强的蜂群算法结合农产品供应链进行实验与分析,获得了较好的优化效果。对比实验结果表明,算法获得较多的总成本与供货时间的帕累托最优解,可提供较多的供应链网络配置方案,同时,算法的鲁棒性与计算效率也具有优势。
[Abstract]:The production and supply of agricultural products require very high cost and supply time. An enhanced bee colony algorithm is proposed to optimize the multi-base and multi-objective supply chain optimization of agricultural products. First of all, the most suitable location in the colony is chosen as the input parameter of neighborhood search, and more search bees are assigned to the target site and fewer search bees are assigned to the non-target location. After a certain number of iterative searches, we give up the places where the improvement is not obvious, so as to avoid falling into the local optimum and improve the convergence speed. Finally, the enhanced bee colony algorithm is combined with the agricultural product supply chain to carry out experiments and analysis. A better optimization effect is obtained. The experimental results show that the algorithm can obtain more Pareto optimal solutions of total cost and supply time, and can provide more supply chain network configuration schemes. At the same time, the robustness and computational efficiency of the algorithm also have advantages.
【作者单位】：韶关学院信息科学与工程学院;
【基金】：广东省自然科学基金(2014A030313700) 广东省科技计划项目(2013B070206076) 广东省哲学社会科学项目(GD13XGL29) 广东省普通高校特色创新项目(2014KTSCX171,2014WTSCX094) 韶关市科技计划项目(2014CX/K252)
【分类号】：F304;TP18

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