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面向需求变化的军队自动化立体仓库货位优化
引用本文:张伟伟,吴晓波,刘玮,张春园. 面向需求变化的军队自动化立体仓库货位优化[J]. 后勤工程学院学报, 2014, 30(5): 60-64
作者姓名:张伟伟  吴晓波  刘玮  张春园
作者单位:后勤工程学院后勤信息与军事物流工程系,重庆,401311
摘    要:为提高军队自动化立体仓库的出库能力,提出应根据需求变化对在库物资货位进行动态调整,从而最大限度地保障军队物资需求。综合考虑堆垛机总行程、货物离散度和出库频率等评价指标,采用遗传算法对该多目标优化问题进行求解,并运用Matalab仿真。结果表明,该方法能较好地提高军队自动化立体仓库在需求动态变化时的出库能力。同时,该研究对一般仓库的货位优化也有一定的借鉴意义。

关 键 词:需求变化  遗传算法  多目标优化  货位优化

Optimization of Military AS/RS Storage Location Oriented at Demand Changes
Zhang Wei-wei,Wu Xiao-bo,Liu Wei,Zhang Chun-yuan. Optimization of Military AS/RS Storage Location Oriented at Demand Changes[J]. Journal of Logistical Engineering University, 2014, 30(5): 60-64
Authors:Zhang Wei-wei  Wu Xiao-bo  Liu Wei  Zhang Chun-yuan
Affiliation:(Dept. of Logistics Information & Logistics Engineering, LEU, Chongqing 401311, China)
Abstract:Stacker' s dynamic adjustment to storage location in accordance with demand changes is proposed to improve the stock removal capability of military AS/RS, and thereby, to support the demand of military material capacity. Based on the evalua- tion indexes of stacker' s total travel, material dispersion, stock removal frequency, etc, the genetic algorithm is used to solve the multi-objective optimization problem and Matlab is employed to simulate it. Results indicate that this method can improve emergen- cy response when demand changes. Also, it has certain reference significance to the storage location optimization of general ware- houses.
Keywords:demand changes  genetic algorithm  multi-objective optimization  slotting optimization
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