基于混合差分进化算法的联合补货-配送优化模型

本文综合考虑联合补货与配送决策,研究了随机需求、允许缺货环境下多企业多产品联合补货与配送集成优化模型,设计了混合差分进化算法(Hybrid Differential Evolution, HDE)对该模型进行求解,同时通过算例与遗传算法、标准的DE算法进行了比较,证实HDE算法高效且稳定;另外,设计了一个先补货再配送的两阶段优化模型,对比优化结果发现采用供应链协同时补货成本较高,配送成本较低,且总成本较低。最后,对相关参数进行了敏感性分析,发现需求率和库存维持成本的变动对总成本的影响远远大过次要订货成本对总成本的影响。

Integrated Joint Replenishment and Distribution Model Using Hybrid Differential Evolution Algorithm

Considering joint replenishment and distribution decision when stock out is allowed,a model integrating multi-buyer joint replenishment and distribution with stochastic demand is analyzed.A hybrid differential evolution(HDE) algorithm is designed to solve the proposed model.An example shows the performance of the HDE is more stable and efficient compared with genetic algorithm and typical differential evolution algorithm.In addition,a two-stage model with replenishment and delivery uncoordinated is designed.The numerical experiments illustrate the fact that the replenishment cost is higher,distribution cost is lower and total cost is lower under supply chain collaboration.Finally,the sensitivity analysis on relevant parameters is addressed and the results show the influence of variations in demand rate and inventory holding cost on the total cost is far greater than that of variations in minor ordering cost on the total cost.