钢铁企业物流库存资源调度优化管理

发布时间：2018-01-17 00:24

本文关键词：钢铁企业物流库存资源调度优化管理　出处：《计算机仿真》2017年07期 　论文类型：期刊论文

【摘要】：钢铁企业物流库存资源调度,关系着企业的物流成本和下游产线物料能否得到及时供应。传统方法没有从车辆分配角度来对资源入库调度的物流成本和调度效率进行分析。选择合适的车辆入厂顺序和入厂时间可以在降低物流成本的同时提高调度效率,为解决上述问题,建立了最小化货车卸货时间跨度和仓库运转成本的整数规划模型,并提出了一种协同改进引力搜索算法对问题进行求解。算法采用变压力的质量公式来平衡探索和开采能力,应用协同方式使群间信息共享加快了算法的运算速度,在种群多样性缺失时引入基于区间对称的反向学习种群,并与原种群共同进行精英选择,保证优秀解不被破坏的同时增大种群多样性。通过一个应用实例使用不同方案的对比实验验证了上述算法的有效性。
[Abstract]:Scheduling of logistics inventory resources in iron and steel enterprises. The traditional method does not analyze the logistics cost and scheduling efficiency of resource storage scheduling from the point of view of vehicle allocation. Plant order and entry time can reduce the cost of logistics and improve scheduling efficiency at the same time. In order to solve the above problems, an integer programming model is established to minimize the time span of cargo unloading and the cost of warehouse operation. A cooperative improved gravitational search algorithm is proposed to solve the problem, which uses the variable pressure mass formula to balance the exploration and mining ability. The collaborative approach is used to accelerate the computation speed of the algorithm. When the diversity of the population is missing, the reverse learning population based on interval symmetry is introduced, and the elite selection is carried out together with the original population. The effectiveness of the proposed algorithm is verified by a comparative experiment of using different schemes in an application example to ensure that the excellent solutions are not destroyed and the population diversity is increased at the same time.
【作者单位】：河北工业大学控制科学与工程学院;
【基金】：河北省科技支撑计划项目(13210307D)
【分类号】：F252;F407.3;TP18
【正文快照】： 1引言物流,被认为是钢铁企业的“第三利润源泉”,如何提高企业的物流运作效率、降低企业的物流成本,越来越受到钢铁企业的重视[1]。库存资源调度优化问题属于钢厂厂内物流的重要组成部分,资源入库调度优化又是其中的重要一环,由此良好的资源入库调度对于钢铁企业来说意义重大

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