基于改进模拟退火遗传算法的自动化立体仓库 货位优化

针对自动化立体仓库出入库作业量大、品类复杂等特点,对仓库货位展开优化研究,遵循周转率原则、货架稳定原则、关联原则等,构建了提高出库效率、提高货架稳定性、增强货物相关性的货位优化模型。使用传统模拟退火算法、遗传算法与改进模拟退火遗传算法求解模型,得出货位优化结果。对比分析结果证明了在解决货位优化问题时,改进算法比传统基础算法更加有效,能更好地改善自动化立体仓库空间使用率低、拣选效率低、货位摆放混乱的现状。     

立体仓库固定货架拣选作业优化研究

目前,我国大部分立体仓库中已基本使用先进的机械化设备,但是对于固定货架的拣选作业优化问题方面的研究却没有得到人们重视。应用TransCAD软件优化求解堆垛机最优拣选作业路径,并进行模拟仿真。     

基于“货到人”拣选系统的动态货位分配研究

目的 为了提高“货到人”拣选系统的订单拣选效率，研究了电商仓库货位初始存储状态为非空情况下的商品货位分配问题。方法 考虑货架上现存商品信息、仓库空余货位数、待补货商品和新收入商品信息，提出基于商品关联度的分散存储策略，以极大化货架上所有存储商品的关联度之和为目标构建商品上架与下架的动态货位分配数学模型，并设计贪婪算法，再采用改进粒子群算法对贪婪算法得到的结果进行优化。结果 基于商品关联度的分散存储策略可以减少货架平均搬运次数29.32%左右。结论 与随机分配策略相比，文中提出的货位分配策略能够有效提升整个电商仓储中心的拣选速度。     

基于改进遗传算法的自动拣选系统 拣选位分配建模与优化

针对某自动拣选系统建立了拣选位分配优化模型,以拣选时间模型作为适应度函数,并通过判断海明距离添加一个惩罚函数对遗传算法进行了改进,对算例进行仿真实验,可以得到货位排序优化后,总拣选时间明显降低了27.85%。结果表明,货物拣选位的分配对自动拣选系统的拣选效率有很大的影响。要想降低总拣选时间,提高自动拣选系统的拣选效率,不能只考虑个别种类货物的位置分配,要从全局的方向去考虑。该研究对配送中心如何提高自动拣选系统的效率提供了理论支持。     

面向仓库货架的商品智能拣选机器人设计

目的 为降低仓储拣选作业的劳动强度、提高拣选准确率,设计一款可代替人工拣货的拣选机器人。方法 基于PaddlePaddle的PP-ShiTu图像识别系统,实现货架商品的精确识别和种类的快速更新;针对低成本机械臂的视觉抓取问题,提出基于“无标定3D视觉+AGV运动控制”的货架商品抓取引导方法;采用二维码自主导航和智能升降系统实现了货架商品的搬运和立体抓取。结果 实验证明,所设计的拣选机器人实现了货架商品的精确抓取和搬运,测试准确率达到了92.25%。结论 基于该方法构建的智能拣选机器人,可以完成仓库货架商品的拣选和搬运。     

旋转货架配货作业的改进临近域算法

旋转货架系统配置配货作业是现代配送中心中一项非常重要的作业活动,文章研究具有多个水平旋转货架系统的配货作业问题,建立对应的模型,在分析该类型作业中整个货架系统配货顺序最优单个货架物品拣选顺序必然最优的特点基础上,设计改进临近域算法,并通过模拟测试,效果良好.     

现代仓储中心存储布局的优化研究

仓储中心的货架摆放布局是影响拣选作业效率的重要因素之一,为研究货架摆放布局对有效存储面积的影响,以鱼骨布局为研究对象,构建其有效存储面积利用率模型,并对其进行仿真验证。结果表明,在鱼骨布局设计的仓库中,主拣选通道角度一定时,拣选通道宽度与货架宽度比例越大,有效存储面积利用率越小;拣选通道宽度与货架宽度比例一定时,主拣选通道角度越趋近于0度或者90度时,有效存储面积利用率越大。由此,鱼骨布局等改进型仓储布局为决策拣选路径提供了新的思路,也从理论上证明了改进型仓储布局实践应用的可行性。     

考虑排产约束的汽车零部件出库订单排序优化北大核心CSSCI

针对TPL仓库面向汽车零部件企业的产前物料拣选和配送作业环节,研究了JIT生产模式下配送送达时间限定和生产线缓冲库容量有限条件下的出库作业拣选订单排序的优化模型及算法。在分析现有拣选订单排序模式的基础上,提出了融合现有模式优点的新作业模式,建立了该模式下拣选订单排序优化模型,并针对这一整数组合优化模型,设计了一套基于贪心理论的算法对其进行求解。通过实际案例分析表明,该模型及算法可以达到减少拣选作业空余时间、提高作业效率、降低作业成本的目的。     

考虑半托盘出库的堆垛机复合作业拣选路径优化研究

结合自动化立体仓库中堆垛机执行出入库作业的实际情况，提出了考虑半托盘出库情况下的堆垛机复合作业拣选路径优化问题，并构建了该问题的数学模型。针对研究问题的特点，利用一种离散烟花算法进行模型求解，采用爆炸算子和变异算子执行烟花的爆炸操作，实现算法的全局搜索和局部搜索；应用精英选择策略和类似轮盘赌策略以提高收敛效果。最后以某烟草物流公司自动化立体仓库的堆垛机拣选作业为例，将离散烟花算法与其他算法的运算结果作对比，验证了该算法更具求解优势。     

考虑排产约束的汽车零部件出库订单排序优化

针对TPL仓库面向汽车零部件企业的产前物料拣选和配送作业环节,研究了JIT生产模式下配送送达时间限定和生产线缓冲库容量有限条件下的出库作业拣选订单排序的优化模型及算法。在分析现有拣选订单排序模式的基础上,提出了融合现有模式优点的新作业模式,建立了该模式下拣选订单排序优化模型,并针对这一整数组合优化模型,设计了一套基于贪心理论的算法对其进行求解。通过实际案例分析表明,该模型及算法可以达到减少拣选作业空余时间、提高作业效率、降低作业成本的目的。     

Storage policies and order picking strategies in U-shaped order-picking systems with a movable base

Prior research on storage policies and order-picking strategies in order-picking systems has concentrated on studying warehouses with parallel shelves that are separated by horizontal and/or vertical aisles. This paper analyses a special case of an order-picking system where the warehouse is divided into zones with shelves being arranged in the shape of a U in each of the zones. The paper assumes that the shelves of the order-picking system are made up of two rows of stillages that can be flexibly exchanged and that the base of the order-picking process can be moved within the aisle prior to the beginning of the order-picking process. We describe the order-picking system in a formal model and propose different storage location assignment policies whose efficiency is compared in a numerical study. The paper pays special attention to the practical applicability of the model and proposes heuristics that can be easily implemented in practice.     

A generalized design and performance analysis model for end-of-aisle order-picking systems

In this paper we present an analytical design algorithm to determine the near-minimum number of pickers required in an end-of-aisle order-picking operation based on a miniload automated storage/retrieval system. The algorithm is based on an approximate analytical model we developed to estimate the expected picker utilization (and the storage/retrieval machine utilization) for general system configurations with two or more pick positions per aisle and/or two or more aisles per picker. For systems with two pick positions, we also investigate the possibility of improving the picker utilization by sequencing container retrievals within each order.     

Picklist generation algorithm with order-consolidation consideration for split-case module-based fulfilment centres

This paper serves as an initial study on order-consolidating time for a module-based order-picking system. In this system, items are stored in modules, and order picking is performed in waves that comprise more than one customer order. Picked items from multiple modules are conveyed to the packaging department for sortation based on customer orders. The order-consolidating time is the main focus as well as the performance measure in this paper. Order-consolidating time is the time difference between the arrival time of the first and the last item at the packaging department that belong to the same customer order. We proposed a heuristic control strategy, namely a pick-list generation algorithm, which will reduce the order-consolidating time. We named our proposed algorithm the push algorithm, which is an improvement algorithm. The push algorithm is compared with the basic algorithm to evaluate its performance. This comparison is extended under different environment settings to provide a robust conclusion. The experimental results indicate that the proposed algorithm consistently out-performs the basic algorithm in every tested environment with at least 17% improvement.     

A study on order-batching methods of order-picking in a distribution centre with two cross-aisles

One common practice in order picking is order batching, in which items of two or more orders are picked together in one picking trip. Order batching can reduce the total order-picking travel distance if orders with similar picking locations are batched together and picked in the same order-picking trip. In this paper, the performance of different order-batching methods that are made up of one seed-order selection rule and one accompanying-order selection rule is investigated. A seed-order selection rule selects the first order (i.e. the seed order) in an order batch, while an accompanying-order selection rule selects the rest of orders (i.e. the accompanying orders) to be added to the order batch. In this paper, one investigates the performance of nine seed-order selection rules and 10 accompanying-order selection rules under two different route-planning methods and two different aisle-picking-frequency distributions. The problem environment is a distribution centre's warehouse which has an I/O point at one of its corners and two cross-aisles—one front cross-aisle and one back cross-aisle. One wants to understand not only the performance of every seed-order selection rule and every accompanying-order selection rule, but also their combined performance. The effects of route-planning methods and aisle-picking-frequency distributions on the performance of seed-order selection rules and accompanying-order selection rules are also investigated. Different random problems were generated and tested for this purpose. It is hoped that the knowledge learned from this study can benefit practitioners in distribution centres with order-batching operations.     

实时路况信息下配送路径的优化

由于物流管理体系的不完善,形成了配送瓶颈,制约了B2C业务的发展,提出了基于现实路网和实时交通信息的情况下,对单一客户服务的动态配送算法.实验结果表明:在路网状况不发生变化的时候,该算法能够和普通算法一样求出最优路径,但是随着路网状况变化的加剧,该算法比普通算法能更好地求出最优配送路径.     

Order picker routing with product returns and interaction delays

E-commerce companies often use manual order-picking systems in their warehouses since these systems can provide the required flexibility and scalability. Manual systems have been widely studied, but the operating policies may require significant changes for e-commerce settings. First, to maintain consumers’ loyalty, it is important to maintain delivery reliability even on the busiest days. When the number of order pickers in an area increases, however, more delays due to interactions may occur. For example, travel speed may need to be lowered when order pickers pass each other in narrow aisles. Second, many products sold through e-commerce are returned by consumers. Before these returned products can be sold again, they must be reintegrated in the stock. This paper presents hybrid genetic algorithms to determine routes for simultaneous pickup of products in response to consumers’ orders and delivery of returned products to storage locations. Furthermore, interactions between the order pickers are considered in the routing decisions. The developed algorithms use specific warehouse problem characteristics. We identify the mix of pickups and deliveries to realise the highest savings in practice. It is shown that order-picker interactions can be a significant cause for delay and should be accounted for in the routing.     

Ant colony optimisation algorithm for distribution-allocation problem in a two-stage supply chain with a fixed transportation charge

In a fixed charge transportation problem, each route is associated with a fixed charge (or a fixed cost) and a transportation cost per unit transported. The presence of the fixed cost makes the problem difficult to solve, thereby requiring the use of heuristic methods. In this paper, an algorithm based on ant colony optimisation is proposed to solve the distribution-allocation problem in a two-stage supply chain with a fixed transportation cost for a route. A numerical study on benchmark problem instances has been carried out. The results obtained for the proposed algorithm have been compared with that for the genetic algorithm-based heuristic currently available in the literature. It is statistically confirmed that the proposed algorithm provides significantly better solutions.     

Adaptive update interval tracking based on adaptive grid interacting multiple model

The update interval is adjustable in the phased array radar system. An adaptive update interval algorithm based on the adaptive grid interacting multiple model is proposed. The moving step size of mid-model's parameter is utilised to adapt the update interval to the target's behaviour. Furthermore, a controllable parameter is introduced to balance the tracking precision and the system load. The effectiveness of the algorithm is verified through simulation. The simulation results also demonstrate that the proposed algorithm can save much system resource while achieving the same tracking quality as the fixed update interval algorithm.     

Efficient architecture for global elimination algorithm for H.264 motion estimation

This paper presents a fast block matching motion esti mation algorithm and its architecture. The proposed architecture is based on Global Elimination (GE) Algorithm, which uses pixel averaging to reduce complexity of motion search while keeping performance close to that of full search. GE uses a preprocessing stage which can skip unnecessary Sum Absolute Difference (SAD) calculations by comparing minimum SAD with sub-sampled SAD (SSAD). In the second stage SAD is computed at roughly matched candidate positions. GE algorithm uses fixed sub-block sizes and shapes to compute SSAD values in preprocessing stage. Complexity of this GE algorithm is further reduced by adaptively changing the sub-block sizes depending on the macro-block features. In this paper adaptive Global Elimination algorithm has been implemented which reduces the computational complexity of motion estimation algorithm and thus resulted in low power dissipation. Proposed architecture achieved 60% less number of computations compared to existing full search architecture and 50% high throughput compared to existing fixed Global Elimination Architecture.     

Design of flexible manpower line walk cycles for a fixed number of operators

Flexible manpower lines (FMLs) are a form of flow process line in which operators are allocated ‘walk cycles’, i.e. a repetitive sequence in which to load and unload machine tools. The effective design of such lines is normally achieved with the expectation that operators without full walk cycles, i.e. those that do not require a full Takt time to accomplish, can complete their walk cycles at an adjoining FML. However, an alternative FML design strategy is possible in cases where no adjoining FML exists or it is not possible for operators to move between work areas. This strategy involves determining the minimum Takt time and the associated operator walk cycles at which the FML can operate under a fixed number of operators. To solve this type of problem, a genetic algorithm that make use of a novel crossover operator has been developed that can design FMLs. The genetic algorithm is capable of generating, for a specific Takt time and fixed number of operators, FMLs with high-quality, near-optimal operator walk cycles. Solutions for the fixed manpower case were then identified by performing multiple genetic algorithm runs to find the best walk cycles at various Takt times.