中文摘要：

分析了基于供应成本优化的备件协同控制库存决策模型,为获得全局收敛能力强、速度快,尤其是稳定可靠的新算法,设计了基于遗传和差分进化算法的混合智能求解算法,并通过两个实例与遗传算法、标准的差分进化算法进行了性能对比,显示出了所提算法的优势。基于所设计的算法,分别对用户需求、运输成本和最晚供应到达时间等参数进行了敏感性分析,讨论了数据不确定性对库存协同控制的影响程度,进而给出了不同环境下的供应方式优化建议。

英文摘要：

A collaborative control model of spare parts inventory based on the total supply cost optimization was analyzed.To find a novel stable,in particular,reliable algorithm with global convergence capability,a hybrid intelligent evolution algorithm was designed based on genetic algorithm and differential evolution algorithm.Two examples revealed performances of the proposed hybrid algorithm compared to genetic algorithm and standard differential evolution algorithm.The sensitivity analysis was performed,influences of data uncertainty on collaborative inventory control policy was also discussed.Finally,the corresponding supply optimization recommendations under different circumstances were presented.