摘要
为了解决自动化立体仓库的随机库存在线动态货位分配问题,针对仓库货物出入库效率、货物分类存储的合理性和货架整体稳定性方面的需求,基于加权归一化处理多目标决策构建了货位分配优化数学模型.提出一种改进的二次优化遗传算法(quadratic optimization genetic algorithm,QOGA),并利用MATLAB软件进行仿真实现.仿真结果表明,该算法收敛速度大幅提高,出入库效率、货架稳定性明显提升,货物分类存储更加合理.由多目标决策结果验证了改进QOGA的先进性和有效性.
This research focuses on the dynamic allocation of random online inventory in automated warehouse.To meet the demands for cargo to enter and leave efficiently,be classified rationaly and stored stably,a mathematical model of cargo location allocation optimization is constructed based on weighted and normalized multi-objective decision-making,and a new quadratic optimization genetic algorithm(QOGA)is proposed for the model.The simulation carried out by MATLAB software shows that the new algorithm improves greatly the convergence rate,the efficiency of storage and the stability of shelves,and the cargo classification and storage are more reasonable.The comprehensive multi-objective decision-making results have verified the advancement and effectiveness of the QOGA.
作者
陈晓艳
张东洋
苏学斌
代钰贺
赵春东
CHEN Xiaoyan;ZHANG Dongyang;SU Xuebin;DAI Yuhe;ZHAO Chundong(College of Electronic Information and Automation,Tianjin University of Science&Technology,Tianjin 300222,China;Qinghai Tongda Oil Processing Co.,Ltd.,Xining 810000,China)
出处
《天津科技大学学报》
CAS
2020年第4期75-80,共6页
Journal of Tianjin University of Science & Technology
基金
青海省科技厅重点研发与转化计划资助项目(2018-NK-C23)。
关键词
货位优化
多目标决策
遗传算法
建模仿真
location optimization
multi-objective decision
genetic algorithm
modeling and simulation
