Abstract: In order to reduce the cost and the waste of production resources caused by uncoordinated production and distribution, an optimization model of distribution considering push production scheduling is established. Aiming at the disadvantage that the conventional simulated annealing algorithm is prone to fall into the local optimum under the influence of random factors, an improved simulated annealing algorithm with tempering and slow cooling operation is designed. This improved algorithm is used to solve the model and determine the reasonable vehicle distribution route and supplies production plan. The contrast experimental results show that compared with the single distribution optimization model, the proposed model considering the push production scheduling can effectively reduce the material retention time caused by the premature production and the delivery delay cost caused by the late production. Compared with the standard simulated annealing algorithm, the improved algorithm can find a better solution, the standard deviation of the calculated results is reduced by 93.42%, showing better stability. And the improved simulated annealing algorithm has lower deviation rate and higher quality in the low-frequency calculation, and the average deviation rate is within 0.5%.

Key words: distribution, production, coordinated optimization, capacitated vehicle routing problems with soft time windows (CVRPSTW), simulated annealing algorithm (SAA)

摘要： 为减小物资生产与配送不协调造成的成本及生产资源浪费,建立了考虑推动式生产调度的物资配送优化模型,并针对标准模拟退火算法受随机因素影响易陷入局部最优的缺点,设计带有回火与缓冷操作的改进模拟退火算法对模型求解,确定了优化的车辆配送路线以及物资生产计划。对比实验结果表明:相对于单纯的物资配送优化模型,考虑推动式生产调度的配送优化模型,能够有效减小物资滞留时间以及配送延误成本;相较于标准模拟退火算法,改进算法搜索到了更优解,且计算结果的标准差减小了93.42%,稳定性更好;同时,改进模拟退火算法具有较低的偏差率,在中小规模算例中求解质量较高,平均偏差率在0.5%以内。

关键词: 配送, 生产, 协调优化, 带软时间窗约束的车辆路径问题, 模拟退火算法