基于模糊逻辑的立体仓库入库货位指派系统的研究

入库货位分配系统是影响自动化立体仓库运行效率的关键因素之一。针对制造业立体仓库的特点，提出了基于模糊逻辑的方法对入库货位进行分配，选取货品重量、货品周转率和货位的仓库空闲状态作为模糊逻辑的输入变量，通过模糊推理，得到货品的入库货位。在数字化车问的运行验证了该入库货位分配方法的有效性和先进性。     

基于遗传退火算法的AS/RS货位分配问题求解

作为自动化立体仓库出入库作业的起点,货位分配对立体仓库的性能和效率都有着重要的影响,文章在分析立体仓库作业特点的基础上,运用遗传退火算法求解优化模型,并基于MATLAB对优化算法进行了实验仿真验证,结果显示,遗传退火算法对解决货位优化分配问题是有效可行的.     

一轨双机自动化立体仓库货位分配优化研究

以一条轨道两台堆垛机模式的自动化立体仓库货架的货位分配问题为研究对象,引入历史专家知识库,减少堆垛机的碰撞、避让、等待,建立以堆垛机出入库的运行距离最短为目标函数的动态货位分配模型。通过比较动态货位分配方法与货位就近分配策略两种方法,动态货位分配策略减少了一轨双机自动化立体仓库中堆垛机的作业路程,计算验证得出动态货位分配是有效的。     

工业生产型立体仓库货位分配及优化

以工业生产型立体仓库为研究对象,针对其出入库口多、存储货物重量差异大和出入库频率高等问题进行研究。在常规的存储策略基础上,制定了多目标优化的分区存储策略,根据"上轻下重"、"上低温,下高温"和"COI分配规则"提出了以出入库频率、货物重量差异和货物温度差异等为规则的存储原则。建立了运用该策略进行货物货位优化的数学模型,结合Pareto最优解的概念对多目标优化问题进行了求解,确定了货物的货位分配。通过在某企业立体仓库的应用表明:该存储策略有效解决了货物存储时的条件冲突问题,完成了货位优化分配,实现了立体仓库的节能及高效运行。     

自动化立体仓库的货位分配优化

为有效解决自动化立体仓库(AS/RS),即自动存取系统的货位分配问题,以货架稳定性和出入库效率为目标,结合多色集合、粒子群算法和模拟退火算法三者优势,建立区域划分、货位分配两阶段的多目标货位分配决策模型。区域划分阶段考虑货物出入库效率和货架受力情况,采用多色集合的围道布尔矩阵进行划分。货位分配阶段根据入库货物的类型和数目,采用结合模拟退火算法的混合粒子群算法求解货位分配优化问题。在MATLAB软件中运行实例,结果证明,与遗传算法和粒子群算法比较,混合粒子群算法在求解货位分配优化问题时的收敛速度快、稳定性高,且能在保证货架稳定性的前提下提高出入库效率。     

基于Flexsim的自动化仓储系统货架货位分配策略的研究

以直线导轨、两端出入库仓库为研究对象,分析了采用不同堆垛机运行模式时堆垛机的作业过程,确定了适用于该型仓库的堆垛机运行模式,在此基础上针对自动化仓储系统的不同业务需求提出了两种货架货位分配策略。利用Flexsim进行仿真,仿真结果表明,在不对自动化仓储系统现有设施升级的情况下,采取合适的货架货位分配策略能有效提高自动化仓储系统的作业效率,为设计提供了参考。     

基于改进灰狼优化算法的自动化立体仓库作业能量优化调度

针对带有截止时间约束的自动化立体仓库出入库作业调度问题,以调度过程中堆垛机能量消耗为优化目标建立数学模型,并引入相应的惩罚函数。对于入库货物,同时考虑定位存储和随机存储两种入库策略,采用一种最近邻货位选择策略对随机存储货物进行合理货位分配。采用一种改进灰狼优化算法对问题进行求解,算法通过引入融合Lévy飞行的混合个体更新策略和多种群重组策略来增强算法的搜索能力。通过仿真实验验证了改进灰狼优化算法在求解自动化立体仓库出入库作业能量优化调度问题的有效性。     

基于混合禁忌搜索算法的自动化立体仓库的货位分配与优化研究

自动化立体仓库是现代物流系统的重要组成部分。文章在对自动化立体仓库的出入库作业方式进行分析的基础上,提出了一种求解自动化立体仓库货位分配与优化的混合禁忌搜索算法HTS(Hybrid Tabu Search)。HTS通过启发式算法生成货位分配的初始解,然后由禁忌搜索算法对货位分配进行优化,从而提高立体仓库的运作效率。在实施应用的过程中,对HTS算法的有效性进行了验证。     

基于两阶段狼群算法的自动化立体仓库作业集成优化

为提高单载具自动化立体仓库动态工况下的进出库效率,针对自动化立体仓库作业集成优化问题建立了仿真优化模型。模型根据货物重质、出入库频率划分货架区域,以指令内最小化单载具堆垛机运行时间为研究目标,设计了一种两阶段狼群算法对其进行优化。该算法使用狼群算法对货位分配和作业调度进行集成优化,求解过程体现出两优化问题之间的关联和反馈。实验结果表明,在不同的订单规模下,相比其他优化方式,两阶段狼群算法能得到满意解,并有效缩短自动化立体仓库的作业时间。     

基于入侵杂草算法的WMS货位优化分配的研究

近年来,仓储管理的发展越来越迅速,在物流业中所居的地位也越来越高。仓库的出入库速度是影响仓库效率的重要因素,因此合理的库位分配可以有效地提高仓库的作业效率。针对仓库货位分配策略问题,以相同产品存储相邻位置、提高产品出入库效率、提高货架稳定性为目标,建立了多目标优化模型;然后使用权重系数法将多目标优化模型转化为单目标优化模型;最后分别通过遗传算法和入侵杂草算法来求解该单目标优化模型,并使用Matlab软件进行了仿真实验。对比两种算法的仿真结果可以看出,采用入侵杂草算法可以有效地解决自动化立体仓库的货位优化分配问题。     

库位配置问题的研究与仿真

库位配置问题是立体仓库作业效率的一个重要影响因素.针对货物存取频率把货物分成A、B、C三类,对应地把库位按其与出入库台的距离也分成A、B、C三区,依据实例进行的仿真实验与实际的运行效果,可以提高运行效率15%左右.     

Storage assignment optimization in a multi-tier shuttle warehousing system

The current mathematical models for the storage assignment problem are generally established based on the traveling salesman problem(TSP), which has been widely applied in the conventional automated storage and retrieval system(AS/RS). However, the previous mathematical models in conventional AS/RS do not match multi-tier shuttle warehousing systems(MSWS) because the characteristics of parallel retrieval in multiple tiers and progressive vertical movement destroy the foundation of TSP. In this study, a two-stage open queuing network model in which shuttles and a lift are regarded as servers at different stages is proposed to analyze system performance in the terms of shuttle waiting period (SWP) and lift idle period (LIP) during transaction cycle time. A mean arrival time difference matrix for pairwise stock keeping units(SKUs) is presented to determine the mean waiting time and queue length to optimize the storage assignment problem on the basis of SKU correlation. The decomposition method is applied to analyze the interactions among outbound task time, SWP, and LIP. The ant colony clustering algorithm is designed to determine storage partitions using clustering items. In addition, goods are assigned for storage according to the rearranging permutation and the combination of storage partitions in a 2D plane. This combination is derived based on the analysis results of the queuing network model and on three basic principles. The storage assignment method and its entire optimization algorithm method as applied in a MSWS are verified through a practical engineering project conducted in the tobacco industry. The applying results show that the total SWP and LIP can be reduced effectively to improve the utilization rates of all devices and to increase the throughput of the distribution center.     

Storage location assignment and order picking optimization in the automotive industry

The objective of this study is to design storage assignment and order picking system using a developed mathematical model and stochastic evolutionary optimization approach in the automotive industry. It is performed in two stages. At the first stage, storage location assignment problem is solved with a class-based storage policy with the aim of minimizing warehouse transmissions by using integer programming. At the second stage, batching and routing problems are considered together to minimize travel cost in warehouse operations. A warehouse in the automotive industry is analyzed, and an optimum solution is obtained from an integer programming model. Due to the computational time required for solving the integer programming problem, a faster genetic algorithm is also developed to form optimal batches and optimal routes for the order picker. The main advantage of the algorithm is the quick response to production orders in real-time applications. The solutions showed that the proposed approach based on genetic algorithms can be applied and integrated to any kind of warehouse layout in automotive industry.     

基于仓库管理的中小机电企业信息集成技术

通过分析现阶段国内机电企业的生产特点,提出了一种基于仓库管理的中小机电企业的信息集成管理框架。将企业信息管理系统、调度系统、仿真系统和仓库自动化系统进行了有效集成,研究了总体的信息集成框架,进一步分析了企业信息管理系统、调度系统和仿真系统的框架。讨论了基于映射的货品-货位耦合分配策略、基于任务分解的调度策略等CIMS关键技术原理、方法及其实现步骤。面向中小机电企业的信息集成体系在一家机电企业的实际实施表明,它可使企业的供应、生产、销售和服务水平大为提高。     

考虑需求相关性的多巷道仓库货位分配问题

根据物料相关性及需求频率，建立了多巷道仓库中货位分配的优化数学模型。模型的优化目标是，既要尽量将关系密切的物料聚集摆放，又要尽量将需求频率高的物料靠近出人库口存储。为求解这一NP问题，提出一种结合启发式算法的混合遗传算法。数值实验表明，该模型与不考虑需求相关性的分配策略相比，可以得到更好的结果，并且随着需求相关性水平的提高，效果更加明显。     

The optimum design of a warehouse system on order picking efficiency

From literature review and deep understanding on the practical industry, it is understood that the proper use of storage assignment policies can use minimum storage space to reach the purpose of minimum total traveling distance, and this has a direct impact on enhancing the order picking performance. At the same time, proper routing planning can minimize overall order picking cost, and finally reach the goal of picking performance enhancement in unit time. Therefore, this paper considers the effects on the order picking system performance for factors such as quantity and layout type of cross aisles in a warehouse system, storage assignment policy, picking route, average picking density inside an aisle, and order combination type, etc. A software, eM-plant, will be used as a simulation and analysis tool, a warehouse design database will be developed, which is based on the minimum overall traveling distance as the optimum performance index, the cross aisle quantity, warehouse layout, storage assignment, picking route planning, picking density and order combination type will be optimally integrated and planned in the warehouse system. Finally, we provide this database to the industry as a reference in the warehouse planning or warehouse design improvement in the future .     

Simulation analysis of mini-load multi-shuttle automated storage and retrieval systems

Technological developments in warehouses have changed processes of storage operations, which reflect in short response times of the storage or retrieval of goods, the reduction of stocks and the volume of storage work as well as the automation of the entire warehouse management. Many companies are replacing traditional warehouses with automated storage and retrieval systems, which can be classified into unit-load and mini-load systems. In this paper, the simulation analysis of mini-load multi-shuttle systems is discussed and evaluated. Multi-shuttle systems are based on the quadruple and sextuple command cycle and could therefore achieve higher throughput capacities due to single-shuttle systems. Different analytical models are used by practitioners for designing multi-shuttle systems. The problem arises with the selection of the appropriate analytical model for which the condition of minimal differences with actual circumstances in practice is fulfilled. For the evaluation of the two well-known analytical models, the discrete event simulations have been used. Beside the evaluation of analytical models, the results of simulation analyses showed throughput improvements for triple-shuttle systems according to dual-shuttle systems. The main objective of this paper is to determine the performance of presented models (analytical and simulation models) of multi-shuttle systems, which represents the main share and support in design process of mini-load multi-shuttle automated storage and retrieval systems.     

基于零件特征的工艺任务分配研究

工艺任务分配是工艺设计活动的重要组成部分,其结果直接影响工艺设计周期.为缩短工艺设计活动周期,实现工艺任务分配的智能化,提出了一种面向零件特征的工艺任务分配方法.任务分配是在PDM系统与CAPP系统集成的环境下,根据对任务分配的影响程度选取特征类型,生成相应的分类矩阵并映射为工艺人员设计能力矩阵.为获取最优的分配方案,对设计能力矩阵采取一种基于淘汰制的改进蚁群算法.结果表明,该算法能较好的收敛到最优解同时大大减少迭代次数.基于零件特征的工艺任务分配方法本质上是依据设计人员的设计能力和专长并采取一种优化算法进行任务分配,为缩短工艺设计周期实现CAPP系统的智能化提供了有力支持.     

一种鱼骨仓储布局下的拣选路径优化方法

根据一种非传统鱼骨(fishbone)布局的特点，基于仓储运作约束条件建立了拣选路径优化模型，构造了非传统货位距离矩阵；在标准遗传算法基础上，通过进化逆转算子克服标准遗传算法存在早熟收敛和局部搜索能力较差等问题，给出了一种多种群遗传算法；为验证算法的有效性，在不同订单规模下，将多种群遗传算法与标准遗传算法和S-Shape算法进行比较，应用MATLAB软件仿真分析，一系列实验结果表明多种群遗传算法计算结果最优，并且寻优速度更快于标准遗传算法，能够很好地解决鱼骨仓储布局下的拣选路径优化问题，提高仓储智能化水平。