Warehouse Layout Research Articles

Cross-Docking Layout Optimization in FlexSim Software Based on Cold Chain 4PL Company

The paper highlights the potential of cross-docking to reduce storage time and costs. The study addresses evolving market demands that push logistics providers to adopt new technologies for operational efficiency, emphasizing the often-overlooked importance of optimizing cross-docking layouts. The research, conducted in two phases, first analyzed the current warehouse layout (Variant I) to identify inefficiencies and then designed a new layout (Variant II) that was simulated using FlexSim 2022 software. The results showed significant improvements with the new layout, including a 35% increase in deliveries and a 3.23% reduction in forklift travel distances, leading to lower operational costs. Even minor adjustments in the warehouse design proved to enhance logistics efficiency, particularly during peak demand periods like holidays. The study demonstrates how FlexSim software can be applied in cold chain logistics to optimize warehouse operations, underscoring the benefits of cross-docking for cost-effective logistics management.

A stochastic analysis of the dynamic space utilization in warehouses

Improving the volume space utilization of modern warehouses is a critical objective in warehouse layout design, making the accurate estimation of space utilization across different layouts essential. However, the dynamic demand and replenishment processes of heterogeneous stock keeping units (SKUs) in modern warehouses present significant challenges in accurately assessing space utilization. Traditional models have relied on deterministic frameworks that assume constant demand and production processes, which do not fully capture the heterogeneity and stochasticity in demand arrivals, sizes, and replenishment times encountered in practical scenarios. This study aims to develop a framework for computing volume space utilization in modern block stacking warehouses, incorporating both heterogeneity and stochasticity. We investigate two models in warehouse scenarios: the lost sale model, where excess demand is lost, and the backorder model, where unmet demand is backlogged. For each model, we derive the closed-form expressions of three key types of space wastes that characterize the space utilization of warehouses: honeycombing, aisle, and top-of-lane space wastes, using a continuous-time Markov chain analytical framework. Utilizing these expressions, we analyze the tradeoffs among these wastes and identify the optimal lane depth that maximizes space utilization. Our case studies show that, in a stochastic environment, the proposed computational framework allows for a more accurate estimation of space utilization, and the application of the obtained optimal lane depth can achieve significantly higher space utilization than deterministic methods found in the literature. This underscores the importance of incorporating stochasticity and heterogeneity of demand and replenishment in layout design. Additionally, by investigating the sensitivity of space utilization to varying demand processes and replenishment strategies, we provide managerial insights for adapting warehouse layout designs in response to changes in SKUs' demand and replenishment patterns.

A novel framework for automated warehouse layout generation.

Optimizing warehouse layouts is crucial due to its significant impact on efficiency and productivity. We present an AI-driven framework for automated warehouse layout generation. This framework employs constrained beam search to derive optimal layouts within given spatial parameters, adhering to all functional requirements. The feasibility of the generated layouts is verified based on criteria such as item accessibility, required minimum clearances, and aisle connectivity. A scoring function is then used to evaluate the feasible layouts considering the number of storage locations, access points, and accessibility costs. We demonstrate our method's ability to produce feasible, optimal layouts for a variety of warehouse dimensions and shapes, diverse door placements, and interconnections. This approach, currently being prepared for deployment, will enable human designers to rapidly explore and confirm options, facilitating the selection of the most appropriate layout for their use-case.

A multi-step mixed integer programming heuristic for warehouse layout optimization

Warehouse layout optimization is critical to inventory and logistics management in organizations. In many instances, limited warehouse space is a constraint and a barrier to expanding operations and increasing demand. We present a multi-step solution using mixed integer programming to improve space utilization and increase order retrieval and fulfillment efficiency. We present a real-world case study to demonstrate the applicability and efficiency of the proposed mixed integer programming heuristics at a large distribution center.

Warehouse layout optimization for fishbone robotic mobile fulfillment systems

The rapid development of electronic commerce has increased demands for order fulfillment efficiency, making this a crucial challenge for warehouse systems. The study proposes a novel fishbone robotic mobile fulfillment system (FRMFS) to optimize warehouse layout and enhance the picking efficiency of automated warehouse systems, such as robotic mobile fulfillment systems (RMFS). Through the construction and analysis of mathematical models, the research demonstrates that FRMFS can significantly reduce the travel distance of robots when compared to traditional RMFS. This leads to an improvement in the overall picking efficiency of the warehouse system. The study also examines the impact of warehouse parameters, cross-aisle angles, and the number of picking stations on system operational efficiency. Simulation experiments confirm that FRMFS can reduce picking distances by 18%–28% compared to traditional RMFS. This makes it particularly suitable for complex warehouse systems with high requirements for operational response time and system throughput. Furthermore, the study introduces a point-based layout design method for picking stations in FRMFS, demonstrating its efficiency as a heuristic approach. This research presents a scientific analysis framework and model support for the operational design and optimization of FRMFS, offering valuable insights for management practices.

Optimizing order picking processes in warehouses: strategies for efficient routing and clustering

The study employed a simulation based on a detailed dataset containing over 307,046 unique order identifiers and 1,050 unique product identifiers. This dataset included information such as order placement dates, product codes, quantities, and precise locations within the warehouse, including coordinates. The simulation modeled the order-picking route using the Single-Picker Routing Problem (SPRP) algorithms to minimize distance and travel time. The methods compared various wave-picking strategies and grouping methods (single-line and multi-line) for their effectiveness.The applied method significantly reduced the travel distance required by the order picker in the warehouse. The key to this optimization was consolidating orders into waves of specific sizes, achieving a fourfold distance reduction for the studied dataset. Additionally, the solution proposed grouping products by location within the warehouse, either in a single aisle or across multiple aisles based on proximity. Although this method often enhances efficiency, it did not in this particular case. However, it was included as it may yield better results with different datasets and further reduce travel distances in the warehouse. The research underscored the critical role of efficient routing and grouping strategies in warehouse operations. Although wave picking significantly reduced travel distances, the effectiveness of clustering strategies depended on the characteristics of the specific dataset, suggesting the need for tailored solutions based on the warehouse layout and the features of the orders. Future research could extend to integrating product volume and weight variations, which may further optimize order-picking strategies.

Pendampingan Perancangan Gudang Material dan Cutting pada Perusahaan Tas TIJ

Top Intera Jaya (TIJ) is a company that focuses on designing and producing high-quality leather bags, wallets, and accessories. TIJ has a monthly production capacity of 50,000 pcs and plans to increase it to 100,000. The company needs better storage capacity and production floor to support this increase. This Community Service Program (CSP) aims to assist TIJ in redesigning the production floor into a raw material and cutting storage warehouse using the shared storage method. The shared storage method organizes warehouse space using the FIFO (First In First Out) principle, where the fastest delivered items are placed in the storage area closest to the exit. This CSP began by conducting interviews with resource persons, namely warehouse staff, to understand the needs of TIJ. After getting an initial overview, the team designed the training materials that TIJ needed. CSP was conducted on February 2, 2024, with the pre-test and post-test results showing an increase in participants' understanding of warehouse design from 33% to 67% and from the results of the training and mentoring, the team and management of TIJ agreed that the shared storage method with the FIFO principle is the best solution that will be implemented for warehouse layout efficiency at TIJ.

Warehouse material handling layout planning using the activity relationship chart method and blocplan 90

This research aims to plan the layout of material handling in a warehouse using the Activity Relationship Chart (ARC) method which is supported by the application of Blocplan 90. In warehouse management, the layout of material handling plays a crucial role in operational efficiency and productivity. The ARC method is used to identify relationships between activities in the material handling process and Blocplan 90 is used as a tool to optimally arrange the warehouse layout. This research will involve analysis of various material handling activities, including storing, picking, and moving goods. By paying attention to the interrelationships between activities revealed by ARC, this research will produce layout recommendations that can increase efficiency, reduce travel time, and minimize the risk of accidents and damage to goods. It is hoped that the results of this research can provide practical guidance for warehouse planners to improve operational performance and optimize the use of storage space. Thus, this research provides a significant contribution in the context of logistics management and operational efficiency in warehouses. The results of this research show that there is a difference in OMH produced in the selected proposed layout, namely IDR 23,748/day from IDR 49,085/day. This shows that there is a reduction in OMH of 52%

Methodology for Designing Spatial Layout of a Warehouse in the Context of Sustainable Development

Theoretical background: The literature analysis focuses on the importance of spatial design of warehouses, especially the retrieval zone. Research shows that warehouse layout has a key impact on operational efficiency, especially in manual order picking. The authors discuss various approaches that are mainly aimed at minimizing the average distance traveled by warehouse employees when picking orders. Other studies also include warehouse workers’ movements and operations planning. The authors note that existing research focuses mainly on operational efficiency, ignoring social and environmental aspects. Hence, there is a need to develop a methodology that will take into account these additional aspects of designing a sustainable warehouse. Purpose of the article: The article in the context of scientific research aims to present the methodology of designing a spatial warehouse system in terms of sustainable development. In a practical context, a tool for assessing the effectiveness of sustainable design was developed. Research methods: A case study was chosen as the research method. Observation and interviews with employees were used. These methods allowed for a better understanding of the analyzed issue and occurring phenomena. In addition, the methods used allowed to verify the developed method of spatial design of the warehouse in terms of sustainable development. Main findings: By achieving scientific and practical goals, the article can contribute to promoting sustainable design in business and architectural practice and contribute to building a more sustainable and effective work environment.

Analisis Penataan Gudang dan Tumpukan Pada Gudang Barang Setengah Jadi PT.Integra Indocabinet.Tbk

The main objective of arranging the warehouse layout is to find the most appropriate method so that the movement of goods in the warehouse runs smoothly. Apart from that, the aim of setting the warehouse layout is also to maximize the warehouse area so that the costs of handling activities remain low. Stacks of goods in the warehouse are stacked with a maximum height of 700 cm and above or approximately 7 items stacked in one pile. If these items continue to be stacked using 7 stacks and above, it can cause many defects to occur. This defect occurs because there are too many items piled up. The pile of items should be stacked with a maximum of 5 piles and above. Therefore, defects that occur can cause delays in delivery times and result in large costs experienced due to these defects

Analysis Of Improving The Layout Of Warehouse Accessories Facilities In PT Delapan Jaya Perkasa Garment

PT Empat Jaya Perkasa Garmen is a company located in Bendungan, Kebayanan Jetis, Pilangsari, Kec. Ngrampal, Sragen Regency, Central Java 57252, operates in the garment industry and its production system is based on make to order. High consumer demand causes the production process to increase. This also affects warehouse management activities. Storage conditions and arrangement of goods that are carried out randomly and irregularly will result in the accumulation of goods or mixing of goods in one rack slot. So, this condition will result in a longer search time. This study discusses improving warehouse layout and arranging goods using the Class Based Storage method for process-focused manufacturing or service facilities. The research was carried out by examining products in the accessories warehouse with the aim of finding out the layout of goods in the accessories warehouse, to fulfill the need for searching for goods accurately by looking for the causes of irregular placement and arrangement of goods, then creating a layout of goods in the accessories warehouse. The arrangement of goods is carried out based on the type of goods by means of one rack slot being used for one type of goods. So that the material handling process runs smoothly.

A real‐life study on the value of integrated optimization in order picking operations under dynamic order arrivals

AbstractOptimizing the order picking operations is indispensable for warehouses that promise a high customer service level. While many areas for improvement have been identified and studied in the literature, a large gap remains between academia and practice. To help with closing this gap, we perform a case‐study in collaboration with a spare‐parts warehouse in Belgium. In this study, we optimize the order picking operations of the company, using the actual warehouse layout and real order data. A state‐of‐the‐art online integrated order batching, picker routing and batch scheduling algorithm is adapted to consider multiple real‐life constraints. More specifically, the dynamic arrival of new orders is considered, and a capacity constraint on the sorting installation should be respected. Furthermore, a new waiting strategy is studied in which order pickers can temporarily postpone certain orders, as combining them with possible future order arrivals may allow for more efficient overall picking performance. Finally, the performance of the current operating policy is compared with that of both a seed batching heuristic and our metaheuristic algorithm by use of an ANOVA analysis. The results indicate that the number of order pickers can be reduced by 12.5% if the new optimization algorithm is used, accompanied by an improvement in the offered customer service level.

Revolutionizing Warehouse Efficiency with Shared and Class-Based Storage

This study addresses inefficiencies in the warehouse layout of a paper production company in Pasuruan, East Java, which led to delayed deliveries. By implementing shared storage (SS) using FIFO and class-based storage (CBS), the research aimed to optimize space and improve material handling efficiency. Data collection involved observation, interviews, and company records. The proposed layout reduced space usage from 59.45% to 16.95% and achieved significant time savings: 17.84% for brown paper, 8.84% for white paper, and 28.51% for custom-colored paper. The findings suggest that a systematic layout can greatly enhance warehouse efficiency. Future studies should consider the cost factors associated with these improvements. Highlights: Space Efficiency: Reduced usage from 59.45% to 16.95%. Time Savings: Up to 28.51% for custom-colored paper. Data-Driven: Used observations, interviews, and records for layout optimization Keywords: Warehouse layout, material handling, shared storage, class-based storage, efficiency improvement

Analysis of the Redesign of the Rice Storage Warehouse Layout Using the Shared Storage Method at PT. XYZ

Analysis of the Redesign of the Rice Storage Warehouse Layout Using the Shared Storage Method at PT. XYZ

Multi-Robot Coordination and Layout Design for Automated Warehousing (Extended Abstract)

With the rapid progress in Multi-Agent Path Finding (MAPF), researchers have studied how MAPF algorithms can be deployed to coordinate hundreds of robots in large automated warehouses. While most works try to improve the throughput of such warehouses by developing better MAPF algorithms, we focus on improving the throughput by optimizing the warehouse layout. We show that, even with state-of-the-art MAPF algorithms, commonly used human-designed layouts can lead to congestion for warehouses with large numbers of robots and thus have limited scalability. We extend existing automatic scenario generation methods to optimize warehouse layouts. Results show that our optimized warehouse layouts (1) reduce traffic congestion and thus improve throughput, (2) improve the scalability of the automated warehouses by doubling the number of robots in some cases, and (3) are capable of generating layouts with user-specified diversity measures. We include the source code at: https://github.com/lunjohnzhang/warehouse_env_gen_public

FIFO Method Improvement and Adjustment Design for PT. ABC Warehouse Plans

Face film company PT. ABC requires an efficient and organized storage system to secure raw materials and finished products. However, warehouses currently experience problems with random storage, which causes human error, overstocking, and potential product damage. This research aims to design layout improvements and adjustments to the FIFO (First in First Out) method in PT A B C's warehouse plan. The research method used is qualitative with observation, interviews and literature study. Observation results show discrepancies in warehouse layout that disrupt operational flow, as well as the need for restructuring and improving the management system. Through design improvements, such as rearranging the layout, more strategic placement of goods, and implementing the FIFO method, it is hoped that it can increase warehouse operational efficiency, reduce the risk of goods damage, and speed up the delivery flow to customers. More comprehensive improvements, including inventory management and staff training, are also needed to ensure the successful implementation of an effective FIFO system. Thus, this research contributes to improving warehouse management and operational efficiency of PT. ABC.

The single picker routing problem with scattered storage: modeling and evaluation of routing and storage policies

Despite ongoing automation efforts, most warehouses are still manually operated using a person-to-parts collection strategy. This process of collecting items of customer orders from different storage locations accounts for the majority of the operating costs of the warehouse. Hence, optimizing picker routes is an important instrument to reduce labor costs. We examine the scattered-storage variant of the single picker routing problem in a one-block parallel-aisle warehouse. With scattered storage, an article can be stored at several storage locations within the warehouse, whereas with classic storage, each article has a unique storage location. We use our recently published network-flow model with covering constraints that is based on an extension of the state space of the dynamic-programming formulation by Ratliff and Rosenthal. With modifications in the state graph, this model serves for both exact and all established heuristic routing methods for picker routing. The latter include traversal, return, largest gap, midpoint, and composite. We show that these routing policies can also be implemented through adaptations in the state space. Extensive computational studies highlight a comparison of the different routing and storage policies (in particular class-based storage policies) in the scattered storage context. Analyses demonstrate which combinations of policies are advantageous for the given warehouse layout. For class-based storage policies, we emphasize how the scattering of articles of different classes should be performed: scattering of C-articles is advantageous with reductions of up to 25%. In contrast, when articles are uniformly distributed, A-articles should be scattered.

Research on Irregular Warehouse Layout Based on Optimised Genetic Algorithm

Logistics is playing a significant role in supporting economic growth and material security during the epidemic period and it has been experiencing a rapid development in recent years. With the issues of personalisation and cost, the economy and society ask for higher requirements for logistics storage systems. The rational design of the functional area layout is an essential step to improve the operational efficiency of the logistics warehousing system. In reality, due to warehouse design and equipment application, there has been a gradual increase in irregular warehouses. By taking an irregular warehouse as an example, combining the operation status quo, this paper clarifies the functional area settings and constructs a 0–1 integer planning model based on the grid and systematic layout planning method with constraints, such as the unique functional attributes of the grid. We optimised the genetic algorithm based on the warehouse irregularity factor and the grids factor, and then solve it through MATLAB. Finally, by using the Flexsim software, simulation metrics were selected for evaluation, the method feasibility is verified.

Optimizing Sample Warehouse Layout At PT BIJ: Comparative Study Of Dedicated And Class-Based Storage

PT. BIJ is an analytical laboratory services company, therefore PT. BIJ needs a good warehouse to be able to accommodate the samples it has PT. BIJ experienced problems with sample storage. Therefore, it is necessary to improve the sample storage system to make it easier to find samples to be analyzed. Using the Dedicated Storege and Class Base Storage methods will help provide grouping for each type of sample and place the samples in the right place so that the sample travel distance is shorter. The results of the research carried out can be obtained that the initial travel distance is 262.98 meters, while the proposed dedicated storage distance is 163.19 meters and the proposed basic class storage distance is 149.95 meters, so there is the largest percentage difference of 42.89%. So it can be concluded that using the class base storage method is better than the dedicated storage method.

Perancangan Tata Letak Gudang Penyimpanan Material pada Perusahaan Air Minum dengan Menggunakan Metode Class Based Storage

PDAM Tirta Musi Palembang is a regional company engaged in the supply of clean water, especially in the Palembang area. The company still has not implemented the warehousing method properly. This is indicated by the presence of material with the highest frequency of picking placed far from the entrance and exit of the warehouse, the occurrence of long queues when picking up material for a unit in the warehouse, the aisle is used as the placement of goods, the labeling of materials is uneven, and placing goods in the area empty without regard to entry and exit. For this reason, it is necessary to improve the layout of the warehouse using the ABC Class-Based Storage method. The use of this method is based on the ease of managing the movement of goods in/out based on the frequency of movement of goods. Based on the results of data processing carried out, the grouping of materials using ABC analysis was obtained, namely Class A (HDPE Pipe, Sealtape, Elbow PE, Ferulle, Knee GS, and PVC Glue), Class B (Foucet Elbow and Knee PVC) and Class C (PVC Pipe, Clam Saddle, Box Meter, GS Pipe, and PVC Headlight). The Material Handling costs incurred in the proposed layout amounted to IDR 45,910687 (61.64% savings) which reduced the total distance by 66.30%. Keywords: ABC Analysis, Class-Based Storage, Material Handling Costs, Warehouse Layout