Analytical models for pick distances in fishbone warehouse based on exact distance contour

The pick distance models for a unit load warehouse employing fishbone layout conventionally use semicircular approximation for distance contour which can result in significant error. This paper develops discrete and continuous pick distance models for fishbone layout under random, full turnover, and class-based storage policies based on exact polygonal distance contour. Class-based storage policy with three classes was found to give pick distance comparable to full turnover policy over a range of demand skews and warehouse shapes studied. The discrete and continuous models are compared considering finite storage space, aisle width and discontinues in the ABC curve for a real life data. The sensitivity of warehouse performance over a range of warehouse parameters is studied. We also outline a methodology for class-based storage design where class partitions can be derived for a warehouse of any dimension from the results of a unit area warehouse.     

Impact of required storage space on storage policy performance in a unit-load warehouse

The performance of a storage policy in a warehouse is usually evaluated on the basis of the average one-way travel distance/time needed to store/retrieve a load. Dividing the storage space into zones based on item turnover frequency can reduce the travel distance. However, for a given number of stored items, a larger number of storage zones also requires more storage space, because of reduced space sharing between the items, which increases travel time. This study considers the required space consumption by storage zoning in comparing the performance of random, full turnover-based and class-based storage policies for a unit-load warehouse operated by a forklift in single-command mode. A generalised travel distance model that considers the required space consumption is developed to compare the performance of these policies. Results show that the one-way travel distance of a random policy decreases with the increase in skewness of the demand curve. By considering the required space consumption, a class-based storage policy performs generally better than a full turnover-based policy. In addition, the optimal warehouse shape factor (ratio of warehouse width to depth) appears to decrease with the skewness of the demand curve. Warehouse managers are advised to adopt a wide-shallow warehouse layout when the item demands are approximately equal, whereas a narrow-deep layout is preferred when the demand curves are steep.     

基于EAHP和免疫算法的野战军械仓库布局优化

目的研究影响野战军械仓库布局的因素及仓库布局的优化方法。方法融合运用专家打分法和层次分析法(EAHP),对弹药保障点的重要度进行评价,综合考虑弹药保障点重要度、弹药需求量、各弹药保障点之间的距离等因素,建立野战军械仓库布局优化模型,并利用免疫优化算法求解模型。结果 Matlab仿真结果表明,运用免疫算法求解野战军械仓库最优布局时,选择合适的原始参数是非常重要的,因为它不仅会影响算法的收敛速度,而且还影响最终的优化结果。结论综合运用EAHP和免疫算法来优化野战军械仓库布局的方法取得了令人满意的优化结果。     

Concurrent manual-order-picking warehouse design: a simulation-based design of experiments approach

The design of manual-order-picking warehouses is a combination of interdependent decisions with enormous possible varieties in design components. The strong interrelationship between these components, in addition to the dynamic and interconnected stochastic nature of the problem; necessitate the utilisation of a simultaneous simulation-based approach. This study proposes a concurrent simulation-based design of experiments approach for the design of manual-order-picking warehouses. The proposed approach can investigate all possible warehousing design combinations with their stochastic nature and interactions; hence, widening the search for performance improvement. The examined design components include warehouse throughput, size, layout, operational policies and manpower/carts. Furthermore, the presented approach captures the probabilistic nature of all the key warehouse functions of receiving, unloading, put away, storage, preparation and picking and shipping; and evaluates the performance of the studied designs using the cycle time for a stock keeping unit in the warehouse. Statistical analysis of the simulation results showed several interesting findings; horizontal layout was preferable over all other types of layouts and small size warehouses perform better than other large sizes. The study has also recommended using high throughput for traditional layout-small size warehouses.     

Assess the effects of different operations policies on warehousing reliability

In this study, an assessment model for analysing the reliability of a warehouse system, focusing on resource capability, under given combinations of storage, routing, batching and zoning process policies, is proposed. A reliability assessment model is developed in order to evaluate the effect of different combinations of operations policies on warehouse reliability. To better reflect the real order pick up operations at the warehouse, a simulation model based on the operation scenarios of a Hong Kong logistics service company is developed. The simulation results are used for supporting the evaluation of warehouse reliability through using the proposed reliability assessment model. The most important finding indicates that order batching together with zoning policies yields greater warehouse reliability particularly when the daily order volume is large. In addition, another important research finding shows that warehouse performance is not constant and can drop when certain combinations of operations policies are adopted. The degrading rate of the resource (forklift) when used according to a given combination of polices is also defined by the proposed assessment method. Hence, the result helps logistics service providers enhance resource durability through modifying operations policies and by implementing proper preventive maintenance policies within a dynamic operations environment.     

The consignment stock of inventories under buyer's warehouse space limitation

In this paper, coordination between a single vendor (or manufacturer) and a buyer (or retailer) via the delivery schedule in a production and distribution system is presented. A continuous deterministic model with centralised decision process is developed. To satisfy the buyer's demands, the product is delivered in discrete batches from the vendor's stock to the buyer's stock subject to consignee's warehouse space capacity constraint. A more general type of consignment stock (CS) policies is analysed. The inventory patterns and the cost structure of production distribution cycles (PDC) are described under the constraint – when the ratio α of the sizes of delayed to just in time (JIT) for the vendor deliveries is given. Also, an analysis how an upper buyer's warehouse space limit can act as a key factor for implementing the generalised CS-policies successfully. Numerical examples are presented to illustrate the performance of model and the results. A comparative study of the results shows that the generalised CS-policies performs better.     

Graph-based solution for performance evaluation of shuttle-based storage and retrieval system

The aim of this study is to provide a graph-based solution for performance evaluation of a new autonomous vehicle-based storage and retrieval system, shuttle-based storage and retrieval system (SBS/RS), under various design concepts. By the graph-based solution, it is aimed the decision-maker (i.e. warehouse manager) evaluates a pre-defined system’s performance promptly and decides on the correct design concept based on his/her requirements from thousands of alternative design scenarios of SBS/RS. The design concepts include number of bays (NoB), aisles (NoA) and tiers (NoT) for the rack design and arrival rate of storage/retrieval (S/R) transactions to an aisle of the warehouse (AR). The performance of the system is evaluated in terms of average utilisation of lifts and average cycle time of S/R transactions. Simulation is utilised for the modelling purpose. Seven NoT, seven NoB and six AR scenarios are considered in the experiments. Hence, 294 experiments are completed to obtain the graphs. By this study, to the best of our knowledge it is the first time a graph-based solution including comprehensive design concepts of SBS/RS is presented.     

Order picking system design: the storage assignment and travel distance estimation (SA&TDE) joint method

Of all the warehouse activities, order picking is one of the most time-consuming and expensive. In order to improve the task, several researches have pointed out the need to consider jointly the layout of the warehouse, the storage assignment strategy and the routing policy to reduce travelled distances and picking time. This paper presents the storage assignment and travel distance estimation (SA&TDE) joint method, a new approach useful to design and evaluate a manual picker-to-parts picking system, focusing on goods allocation and distances estimation. Starting from a set of picking orders received in a certain time range, this approach allows to evaluate the combinations of product codes assigned to storage locations, aisles, sections or warehouse areas and to assess the most relevant ones, for the best location and warehouse layout, with the aim of ensuring optimal picking routes, through the application of the multinomial probability distribution. A case study is developed as well, in order to clarify the concept that underlies the SA&TDE joint method, and to show the validity and the flexibility of the approach, through the calculation of the saving at different levels of detail.     

Risk control for staff planning in e-commerce warehouses

Internet sale supply chains often need to fulfil quickly small orders for many customers. The resulting high demand and planning uncertainties pose new challenges for e-commerce warehouse operations. Here, we develop a decision support tool to assist managers in selecting appropriate risk policies and making staff planning decisions in uncertain conditions. Multistage stochastic modelling has been used to analyse risk optimisation approaches and expected value-based optimisation. Exhaustive numerical and practical validations have been performed to test the tool’s applicability. We demonstrate, using a Dutch e-commerce warehouse, that the multi-period conditional value at risk appears to be most applicable.     

Numerical simulation and design optimisation of an integrally-heated tool for composite manufacturing

Tooling design is crucial for the production of cost-effective and durable composite products. As part of the current search for cost reduction, integrally-heated tooling is one of the technologies available for ‘out-of-autoclave’ processing of advanced thermoset polymer composites. Despite their advantages, integrally-heated tools can suffer from uneven distribution of temperature, variability in heat flow rate and inconsistency in heating/cooling time. This research, therefore, investigates a number of design variables such as shape and layout of heating channels in order to improve the thermal performance of an integrally-heated tool. Design of Experiments (DoE) has been carried out using Taguchi’s Orthogonal Array (OA) method to set several combinations of design parameters. Each of these design combinations has been evaluated through numerical simulation to investigate heating time and mould surface temperature variation. The simulation results suggest that the layout of the channels and their separation play a vital role in the thermal performance. Signal-to-Noise (S/N) ratio and analysis of variance (ANOVA) have been applied to the results obtained to identify the optimal design combination of the integrally-heated tool. Statistical analysis reveals that the heating performance of an integrally-heated tool can be significantly improved when the channels’ layout is parallel. The shape of the channels has negligible effect and the distance between the channels should be determined based on the production requirement.     

基于鱼骨型仓库布局的多车拣选路径问题优化

为了推动鱼骨型仓库在实际场景下的应用,针对鱼骨型仓库布局下的拣货路径优化问题,构建待拣货点距离计算模型和以有载重、容积限制的多车拣货距离最短为总目标的拣选路径优化模型。考虑遗传算法(GA)全局搜索能力强、粒子群算法(GAPSO)收敛速度快以及蚁群算法(ACO)较强的局部寻优能力,提出一种解决拣选路径优化模型的混合算法(GA-PSO-ACO)。通过不同订单规模的仿真实验,得出该混合算法在适应度值、迭代次数、收敛速度等方面均优于GA算法和GAPSO算法,且在订单规模较大时,平均适应度值约降低8%,有效缩短了总拣选距离,验证了混合算法在解决鱼骨型仓库布局下的拣货路径问题的先进性和有效性,为解决此类仓库内部的拣货路径问题提供新的解决方法和思路。     

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。     

Analytical models for a new turnover-based hybrid storage policy in unit-load warehouses

This paper considers a low-level unit-load warehouse employing single-deep storage lanes and a single-command manual storage and retrieval policy. Analytical travel distance models are developed for class-based and full turnover storage policies under across-aisle, within-aisle and a newly proposed hybrid product placement schemes. Our computational studies show that the analytical models developed in this paper are very accurate as compared to simulation results and a comparative study with a real-world warehouse case. Hybrid storage policies proposed in this paper outperform all other traditional storage policies. The paper also presents insights and simple design rules to warehouse practitioners.     

Optimising two dwell point policies for AS/RSs with input and output point at opposite ends of the aisle

Automated storage and retrieval systems (AS/RSs) are widely used for storing and retrieving products in all types of warehouses. Dwell point policy is a vital control policy that can greatly affect the performance of AS/RSs. In this paper, we study dwell point policies in AS/RSs with input and output stations at opposite ends of the aisle. We first propose two dwell point policies. We find that five existing dwell point policies in the literature are special cases of exactly one of our policies. We then develop expected travel time models for the proposed policies, solve these models with the objective of minimising expected travel time, and obtain closed-form solutions for the optimal dwell location(s). We prove that one proposed policy dominates the other in terms of expected travel time. Numerical experiments are performed to quantify the percentage gap of expected travel time between the proposed policies and policies in the literature. We find that, in some situations, the better proposed policy can achieve up to 8%–10% reduction in expected travel time in comparison with the best literature policy. A real-data case study validates that these situations arise with high probability in typical daily warehouse operations.     

Warehouse performance measurement: a literature review

As the supply chains get more complex, the variety of indicators and tools to measure warehouse performance has also increased. Furthermore, the metrics that are used for performance evaluation are assessed in different manners and hence there is not clear definition for some of these metrics. To address these issues, this literature review focuses on operational warehouse performance measurement, for which the warehouse managers need to carry out periodic analysis. Using the content analysis method, performance indicators are acquired from selected papers and are classified according to time, cost, quality and productivity dimensions. The contributions of this literature review are as follows: we present a synthesis of the literature on operational warehouse performance, we provide the definitions for the performance indicators and a framework to demonstrate their boundaries and, finally, based on the literature analysis, we also provide some discussions on current trends in warehouses and propose future research directions on warehouse performance evaluation.     

A piecewise nonlinear model for a production system under maintenance,trade credit and limited warehouse space

Small and medium size manufacturers exist commonly in developing countries. Limited warehouse space is a characteristic in small and medium size manufacturers. In today’s business environment, many upstream companies offer a credit period to downstream companies. In production system, a manufacturer usually adopts the system maintenance when the system is in the out-of-control state. Therefore, this paper considers a production-inventory model for a manufacturer under system maintenance, trade credit and limited warehouse space. The objective is to determine the optimal production run time to minimise the total cost. We develop an algorithm based on several theorems for solving the problem described. We provide several examples to illustrate the solution procedure and discuss how system parameters affect the manufacturer’s decision behaviour. Computational analysis demonstrates that the results of the proposed model are consistent with economic insights.     

The effect of warehouse cross aisles on order picking efficiency

This paper investigates the effects of adding cross aisles to the layout of an order consolidation warehouse, with respect to order picking efficiency. Intuitively, cross aisles provide greater flexibility in the routing of order pickers, thus providing shorter order picking travel distances. However, this effect may be negated when the number of cross aisles becomes excessive, as the cross aisles themselves must be traversed in order to reach the required items. A shortest path pick sequencing model is developed which allows for any number of cross aisles in the warehouse. The optimal routing is computed for a large number of randomly generated picking requests, over a variety of warehouse layout and order picking parameters. The results are used to characterize the optimal number of warehouse cross aisles, as well as the conditions under which cross aisles generate the greatest benefit.     

Travel time models for deep-lane unit-load autonomous vehicle storage and retrieval system (AVS/RS)

Autonomous vehicle storage and retrieval systems use vehicles that move horizontally along rails within the storage racks, while vertical movements are provided by lifts. The solution proposed in this paper addresses a particular system configuration that works with multiple deep storage lanes that are widely used in the food and beverage industry, characterised by large volumes of products of limited variety. The generic deep lane is single item, i.e. one stock keeping unit, and single batch, i.e. one production lot, thereby affecting the performance of the system in terms of storage capacity utilisation and throughput. Determining the number and depth of the lanes is crucial to aid the design and control of such a storage system. The aim of this paper was to support the design of AVS/RSs though a set of original analytic models for the determination of the travelled distance and time for single-command and dual-command cycles given alternative layout configurations. The models are validated by simulation and exemplified with a real-warehousing case study. The paper presents useful guidelines for the configuration of the system layout including the determination of the optimal shape ratio and the length of the lanes.     

Material handling improvement in warehouses by parts clustering

A major part of warehouse operations is related to the collection of parts from the warehouse which is called the Order Picking Problem. To improve order picking operations, the total travel distance and generally picking time must be reduced. In this paper, a two-level approach is proposed that determines the locations of parts in the warehouse. The first step clusters parts into part families. Four different clustering methods based on principal component analysis, singular value decomposition and Two-Step Cluster Component are applied. In the second step, four different heuristics are proposed to determine the locations of parts. In addition to the minimisation of travel distance, we also consider the minimisation of the total congestion in aisles due to multiple workers. The proposed algorithms also consider the interactions between part families to minimise intergroup movements. As a result of the implementation, we achieved more than 40% reduction in material handling compared to the current set-up of the warehouse. The applied algorithms can easily be modified to be used for warehouses with different configurations. The algorithms utilised in this case study can be helpful to researchers to become familiar with new heuristics, as well as practitioners to design improved warehouses.     

The impact of the number of parallel warehouses on total inventory

In the strategic design of a distribution system, the right number of stock points for the various products is an important question. In the past decade, a strong trend in the consumer goods industry led to centralizing the inventory in a single echelon consisting of a few parallel warehouses or even a single distribution center for a Europe-wide distribution system. Centralizing inventory is justified by the reduction in total stock which mostly overcompensates the increasing transportation cost. The effect of centralization is usually described by the “Square Root Law”, stating that the total stock increases with the square root of the number of stock points. However, in the usual case where the warehouses are replenished in full truck loads and where a given fill rate has to be satisfied, the Square Root Law is not valid. This paper explores that case. It establishes functional relationships between the demand to be served by a warehouse and the necessary safety and cycle stock for various demand settings and control policies, using an approximation of the normal loss function and its inverse. As a consequence, the impact of the number of parallel warehouses on the total stock can be derived. The results can be used as tools in network design models.