Turnover-based Storage Research Articles

An efficient data-driven method for storage location assignment under item correlation considerations

This research investigates the storage location assignment problems of correlated-items under a realistic multiple-cross-aisle warehouse setting. To accommodate the shortest picking route decision and update customer orders in each replenishment cycle to capture the changing trend in customer preferences. An item-correlations considered fitness function is developed to evaluate the benefit of exchanging item locations and minimise the picking costs. A data-driven storage location assignment method called storage location assignment for correlated-item method is proposed to improve the order picking efficiency. The explicit considerations make this work distinct from existing studies: (1) correlation among items in customer orders, (2) penalty for crossing-aisles in warehouse traffic, and (3) real retail dataset adopted. Our method considers the effect of correlated items in customer orders, through a storage exchange benefit function to evaluate the fitness of storage location to minimise warehouse operation costs and enhance operation efficiency. With a real ecommerce dataset, the numerical study results show that our method can reduce the travelling distance by 5–10% compared with a conventional turnover-based storage policy. Our method not only outperforms in terms of travel distance. The picking time improvement is even more significant for large warehouse if a moderate penalty for crossing-aisles is considered.

Designing an automated storage/retrieval system with a single aisle-mobile crane under three new turnover based storage policies

ABSTRACT This article considers a multi-aisle AS/RS employing a single aisle-mobile crane and develops analytical travel time models for three new storage policies with turnover-based product allocation to aisles. In addition to product turnover, these storage policies also take into account the demand skewness and the characteristics of storage and transport equipment. Based on the proposed travel time models, analytical expressions are derived to determine the physical dimensions of the AS/RS that are optimized with respect to crane travel time. AS/RS designs employing the newly developed storage policies are compared with designs employing three other (non-turnover based) storage policies, using a design methodology proposed in a recent study. The analysis shows that among the three turnover-based storage policies, class-based storage assignment performs better than full turnover-based storage policy when subjected to different evaluation criteria. It is concluded that the inclusion of storage policies in the AS/RS design process, is highly beneficial in the selection of the right storage and transport equipment.

The impact of integrated cluster-based storage allocation on parts-to-picker warehouse performance

Order picking is one of the most demanding activities in many warehouses in terms of capital and labor. In parts-to-picker systems, automated vehicles or cranes bring the parts to a human picker. The storage assignment policy, the assignment of products to the storage locations, influences order picking efficiency. Commonly used storage assignment policies, such as full turnover-based and class-based storage, only consider the frequency at which each product has been requested but ignore information on the frequency at which products are ordered jointly, known as product affinity. Warehouses can use product affinity to make informed decisions and assign multiple correlated products to the same inventory “pod” to reduce retrieval time. Existing affinity-based assignments sequentially cluster products with high affinity and assign the clusters to storage locations. We propose an integrated cluster allocation (ICA) policy to minimize the retrieval time of parts-to-picker systems based on both product turnover and affinity obtained from historical customer orders. We formulate a mathematical model that can solve small instances and develop a greedy construction heuristic for solving large instances. The ICA storage policy can reduce total retrieval time by up to 40% compared to full turnover-based storage and class-based policies. The model is validated using a real warehouse dataset and tested against uncertainties in customer demand and for different travel time models.

Closed form models for dwell point locations with turnover-based storage assignment policy

This study investigates where an idle storage-retrieval device should dwell (locate) to minimise the expected response time of its next transaction for both an automated storage/retrieval system (AS/RS) and an automated storage carousel (ASC). A review of the relevant literature showed that previous attempts to obtain the dwell point location only considered a randomised storage assignment policy. This research proposes that under a myriad of operating conditions, the problem can be formulated as a p-median location problem on a tree network to incorporate the turnover-based storage assignment policy.

Closed form models for dwell point locations with turnover-based storage assignment policy

Closed form models for dwell point locations with turnover-based storage assignment policy

Designing the optimal multi-deep AS/RS storage rack under full turnover-based storage policy based on non-approximate speed model of S/R machine

The design of an optimal rack for 3D multi-deep AS/RS under full turnover-based storage policy is explored in this paper. The acceleration and deceleration characteristics of storage and retrieval (S/R) machine are considered based on non-approximate speed model of S/R machine. We divided three typical scenarios to investigate. With regards to each scenario, we derive the expected retrieval time for single-command cycles adopting exact speed model and develop the model for optimally designing 3D multi-deep AS/RS rack. From the model, we can derive the optimal rack dimensions for various scenarios more precisely. Our findings are demonstrated by a practical example.

Design of an order-picking warehouse factoring vertical travel and space sharing

This paper considers the layout design problem of a single block order-picking rack-based warehouse that employs turnover-based storage assignment in both vertical and horizontal dimensions. An analytical expression for vertical travel distance is derived which is incorporated in the pick distance model. The effect of inventory staggering on storage space requirement is considered in arriving at warehouse dimensions. A model that incorporates area cost along with handling cost in optimizing warehouse design is developed and a solution algorithm is presented. The analytical model for vertical travel and the optimization model are applied to data from a real life case. It was found that the model would offer considerable operational cost savings, especially when space costs are high. Computational experiments show that the effect of inventory staggering is quite significant in the estimated storage space. Experiments also demonstrated the importance of segregating products based on turnover in the vertical dimension.

Order picking under random and turnover-based storage policies in fishbone aisle warehouses

A recent trend in the layout design of unit-load warehouses is the application of layouts without conventional parallel pick aisles and straight middle aisles. Two examples for such designs are flying-V and fishbone designs for single- and dual-command operations. In this study, it is shown that the multi-item order picking problem can be solved in polynomial time for both fishbone and flying-V layouts. These two designs are compared with the traditional parallel-aisle design under the case of multi-item pick lists. Simple heuristics are proposed for fishbone layouts that are inspired by those put forward for parallel-aisle warehouses and it is experimentally shown that a modification of the aisle-by-aisle heuristic produces good results compared with other modified S-shape and largest gap heuristics when items have uniform demand. Computational experiments are performed in order to compare the performances of fishbone and traditional layouts under optimal routing and it is shown that a fishbone design can obtain improvements of around 20% over parallel-aisle design in single-command operations but can perform as high as around 30% worse than an equivalent parallel-aisle layout as the size of the pick list increases. The sensitivity of the results to varying demand skewness levels when volume-based storage is applied is tested and it is shown that unlike the single- and dual-command cases, a fishbone design performs better compared to a traditional design under highly skewed demand as opposed to uniform demand.

On the suboptimality of full turnover-based storage

Full turnover-based storage has been widely claimed to outperform the commonly used ABC class-based storage policy in terms of the resulting storage and retrieval travel time. In the first paper describing the full turnover-based policy, simultaneously implicitly assuming shared storage (that is to say storage space that can be used by other products once the original product's inventory is depleted) was modelled, since no specific space was reserved to store the maximum inventory of a product. However, full turnover-based storage is a dedicated storage policy where the storage space allocated to one product must be able to accommodate its maximum inventory level. Since then, many authors have cited the results of the full turnover-based storage policy while often overlooking its incompatible shared-storage assumption. This paper adapts classic travel time models to accommodate full turnover-based dedicated storage. We consider different warehousing system configurations such as square-in-time (SIT) and non-SIT racks, and speed acceleration and deceleration effects to calculate the storage/retrieval (S/R) machine's travel time. Surprisingly, but in line with practice, the results of the adapted travel time models show that random and class-based storage normally outperform full turnover-based storage.

Turnover-based storage in non-traditional unit-load warehouse designs

This article investigates the effect of assigning the most-active items to the best locations in unit-load warehouses with non-traditional aisles. Specifically, the performance of flying-V and fishbone designs are investigated when products exhibit different velocity profiles. Both single- and dual-command operations are considered for a warehouse where receiving and shipping are located at the midpoint of one side of the warehouse. For dual-command operations, a fishbone design shows similar reductions in travel distances for both random and turnover-based storage policies. The fishbone designs that provide the best performance have a diagonal cross aisle that extends to the upper corners of the picking space and are approximately half as tall as they are wide. In general, warehouse design parameters that perform best under random storage also perform well under turnover-based storage.

Designing an optimal turnover-based storage rack for a 3D compact automated storage and retrieval system

Compact, multi-deep (3D) automated storage and retrieval systems (AS/RS) are becoming increasingly popular for storing products. We study such a system where a storage and retrieval (S/R) machine takes care of movements in the horizontal and vertical directions of the rack, and an orthogonal conveying mechanism takes care of the depth movement. An important question is how to layout such systems under different storage policies to minimize the expected cycle time. We derive the expected single-command cycle time under the full-turnover-based storage policy and propose a model to determine the optimal rack dimensions by minimizing this cycle time. We simplify the model, and analytically determine optimal rack dimensions for any given rack capacity and ABC curve skewness. A significant cycle time reduction can be obtained compared with the random storage policy. We illustrate the findings of the study by applying them in a practical example.

Optimization of warehouse storage capacity under a dedicated storage policy

The problem of the determination of the space requirements for warehouse systems operating under a dedicated storage policy, full turnover-based storage, is investigated. Space shortage occurs when demand exceeds the warehouse storage capacity. The additional space requirement is satisfied by considering a leased storage space. The warehouse storage capacity problem is then formulated as a non-linear programming model to minimize the total cost of owned and leased storage space. An iterative search procedure, which always generates the optimal solution, is developed. Illustration of the approach for systems operating under the standard economic-order-quantity inventory model is provided. The results obtained using the optimization approach presented can be used for determining bounds or approximations for the first-cut design of the storage space requirements.

Back-of-the-envelope miniload throughput bounds and approximations

We derive simple formulas bounding and approximating the throughput of an end-of-aisle miniload system with exponentially distributed pick times and either uniform or turnover-based storage. For typical configurations, the worst-case relative error for the bounds is less than 4%. We use our bounds to show that, for all practical purposes, regardless of the configuration, the picker utilization determines the storage/retrieval machine utilization, and vice versa. Thus, a system designer cannot hope to independently achieve separate goals for the utilization rates.

Dual command travel times and miniload system throughput with turnover-based storage

We analyze travel times for automated storage/retrieval systems. In particular, we apply our travel time model to turnover-based storage systems and determine the mean and variance of dual command travel times. We present detailed numerical results for selected rack shape factors and ABC inventory profiles. We then investigate the effect of alternative rack configurations on travel time performance measures. We also show how to determine the throughput of miniload systems with turnover-based storage and exponentially distributed pick times.

Shared Storage Policies Based on the Duration Stay of Unit Loads

This paper addresses duration-of-stay-based shared storage policies for a unit load warehouse. We show that, for single command storage and retrieval, shared storage policies based on duration of stay of individual unit loads have the potential to significantly decrease travel time. An optimal storage policy with respect to travel time and storage space is developed for systems with balanced input and output. Based on the same principles, two heuristic policies are developed for more complex systems. Simulation results are provided which compare travel times for dedicated storage, random storage, turnover-based storage classes, and duration-of-stay-based storage classes.