钢铁企业物流库存的车辆调度优化
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摘要
作为整个钢铁企业生产过程的准备阶段,车辆入库环节关系着下游生产线的资源配置和库存的运转效率。传统的调度策略没有从车辆入库顺序和时间角度对库存调度的物流成本和效率进行分析,导致调度效率低,成本高,而选择合适的车辆入厂入库顺序和时间并考虑多车共同作业可以有效的提高库存效率且节省成本。为此首先建立了最小化货车出厂时间和传送带最小运转成本的整数规划模型,然后提出了改进萤火虫优化算法对复杂模型进行求解,通过自适应策略改进算法使其增强个体搜索能力,同时在萤火虫移动的过程中引入了Levy变异,避免算法陷入局部最优而无法寻到最优解,最后由测试函数和仿真实例进行测试。结果表明,改进算法可以迅速找出最优调度方案,从而指导企业合理安排资源入库,优化了物流库存管理。
As the preparation phase of the whole iron and steel enterprise production process,the vehicle storage link relates to the resource allocation of the downstream production line and the operating efficiency of the inventory.The traditional scheduling strategy does not analyze the logistics cost and efficiency of inventory scheduling from the aspects of vehicle storage order and time,resulting in low scheduling efficiency and high cost. Choosing the right order and time of arrival of the vehicle into the factory and considering the multi-vehicle co-operation can effectively improve the efficiency of inventory and save cost. For this reason. In the paper,we firstly established an integer programming model that minimizes the factory time and the minimum operating cost of the conveyor,and then proposed an improvement of the Glowworm Swarm Optimization to solve the complex model. The adaptive strategy was used to improve the algorithm to enhance the individual's searching ability. At the same time,Levy mutation was introduced in the process of firefly movement to avoid the algorithm from falling into local optimals. Finally,tests were carried out with test functions and simulation examples. The results show that the improved algorithm can quickly find out the optimal scheduling scheme,so as to guide the enterprises to arrange the resource storage and optimize the logistics inventory management.
As the preparation phase of the whole iron and steel enterprise production process,the vehicle storage link relates to the resource allocation of the downstream production line and the operating efficiency of the inventory.The traditional scheduling strategy does not analyze the logistics cost and efficiency of inventory scheduling from the aspects of vehicle storage order and time,resulting in low scheduling efficiency and high cost. Choosing the right order and time of arrival of the vehicle into the factory and considering the multi-vehicle co-operation can effectively improve the efficiency of inventory and save cost. For this reason. In the paper,we firstly established an integer programming model that minimizes the factory time and the minimum operating cost of the conveyor,and then proposed an improvement of the Glowworm Swarm Optimization to solve the complex model. The adaptive strategy was used to improve the algorithm to enhance the individual's searching ability. At the same time,Levy mutation was introduced in the process of firefly movement to avoid the algorithm from falling into local optimals. Finally,tests were carried out with test functions and simulation examples. The results show that the improved algorithm can quickly find out the optimal scheduling scheme,so as to guide the enterprises to arrange the resource storage and optimize the logistics inventory management.
引文
[1]冯亮,梁工谦.联网中物流配送车辆调度目标定位设计与仿真[J].计算机仿真,2017,34(4):377-381.
[2]刘国莉,唐立新,张明.钢铁原料库存问题研究[J].东北大学学报(自然科学版),2007,28(2):172-175.
[3]张可,徐彬,丁传勇.基于Petri网的钢铁企业原料供应物流优化[J].物流技术,2008,27(7):94-95.
[4]殷脂,等.多配送中心物流配送车辆调度问题的分层算法模型[J].系统管理学报,2014,(4):602-606.
[5]蔺宇,徐天依.循环取货带有时间窗约束的入库道口车辆调度[J].工业工程与管理,2015,20(1):28-33.
[6]刘佳,等.基于模拟退火算法的萤火虫群优化算法研究[J].计算机仿真,2014,(5):284-287.
[7] I Rhee,et al. On the Levy-Walk Nature of Human Mobility[J].IEEE/ACM Transactions on Networking,2011,19(3):630-643.
[8] J J Ranjani,M S Chithra. Bayesian denoising of ultrasound images using heavy-tailed Levy distribution[J]. Image Processing Iet,2014,9(4):338-345.
[9]费腾,张立毅,陈雷.混合Levy变异与混沌变异的改进人工鱼群算法[J].计算机工程,2016,42(7):146-152.
[10]吴聪,杨建辉.基于改进粒子群算法的物流配送车辆调度优化[J].计算机工程与应用,2015,51(13):259-262.
[11]谈晓勇,林鹰.基于混沌蚁群算法的应急救援车辆调度优化[J].计算机应用研究,2014,31(9):2640-2643.
[2]刘国莉,唐立新,张明.钢铁原料库存问题研究[J].东北大学学报(自然科学版),2007,28(2):172-175.
[3]张可,徐彬,丁传勇.基于Petri网的钢铁企业原料供应物流优化[J].物流技术,2008,27(7):94-95.
[4]殷脂,等.多配送中心物流配送车辆调度问题的分层算法模型[J].系统管理学报,2014,(4):602-606.
[5]蔺宇,徐天依.循环取货带有时间窗约束的入库道口车辆调度[J].工业工程与管理,2015,20(1):28-33.
[6]刘佳,等.基于模拟退火算法的萤火虫群优化算法研究[J].计算机仿真,2014,(5):284-287.
[7] I Rhee,et al. On the Levy-Walk Nature of Human Mobility[J].IEEE/ACM Transactions on Networking,2011,19(3):630-643.
[8] J J Ranjani,M S Chithra. Bayesian denoising of ultrasound images using heavy-tailed Levy distribution[J]. Image Processing Iet,2014,9(4):338-345.
[9]费腾,张立毅,陈雷.混合Levy变异与混沌变异的改进人工鱼群算法[J].计算机工程,2016,42(7):146-152.
[10]吴聪,杨建辉.基于改进粒子群算法的物流配送车辆调度优化[J].计算机工程与应用,2015,51(13):259-262.
[11]谈晓勇,林鹰.基于混沌蚁群算法的应急救援车辆调度优化[J].计算机应用研究,2014,31(9):2640-2643.