Warehouse Logistics Research Articles

Lidar Based Position Estimation in Warehouse Logistics

This study introduces a lidar-based algorithm developed to overcome the difficulties encountered in localizing autonomous robots in complex environments. The testing procedure involves identifying lines coming from points, determining the intersections of these lines, and then calculating the location. The location calculation process was carried out by comparing the instantly obtained intersection points with the previous intersection points. The results obtained from the developed algorithm serve to explain the practical application of the algorithm and demonstrate its ability to achieve precise location detection in real-world scenarios. The findings highlight the effectiveness of the algorithm and its potential to contribute to the advancement of autonomous robot navigation in complex environments.

MAGRU: Multi-layer Attention with GRU for Logistics Warehousing Demand Prediction

MAGRU: Multi-layer Attention with GRU for Logistics Warehousing Demand Prediction

AGV Path Planning based on Improved Ant Colony Algorithm

With the widespread application of Automated Guided Vehicles (AGV) in industrial production and warehouse logistics, the challenges they face during operation are becoming increasingly apparent. Currently, the path planning problem of AGV has become one of the hot topics in academic research. This paper provides an in-depth analysis of the performance of AGV in real-world scenarios and utilizes grid-based methods to construct a map environment model. Subsequently, a detailed analysis of the movement of AGV in the environment is conducted, and an improved pheromone method is proposed based on the traditional ant colony algorithm, aiming to optimize the navigation path of AGV to determine the optimal travel route.

EGCY-Net: An ELAN and GhostConv-Based YOLO Network for Stacked Packages in Logistic Systems

Dispatching, receiving, and transporting goods involve a large amount of manual effort. Within a logistics supply chain, a wide variety of transported goods need to be handled, recognized, and checked at many different points. Effective planning of automated guided vehicle (AGV) transportation can reduce equipment energy consumption and shorten task completion time. As the need for efficient warehouse logistics has increased in manufacturing systems, the use of AGVs has also increased to reduce working time. These processes hold automation potential, which we can exploit by using computer vision techniques. We propose a method for the complete automation of box recognition, covering both the types and quantities of boxes. To do this, an ELAN and GhostConv-based YOLO network (EGCY-Net) is proposed with a Conv-GhostConv Stack (CGStack) module and an ELAN-GhostConv Network (EGCNet). To enhance inter-channel relationships, the CGStack module captures complex patterns and information in the image by using ghost convolution to increase the model inference speed while retaining the ability to capture spatial features. EGCNet is designed and constructed based on ELAN and the CGStack module to capture and utilize hierarchical features efficiently in layer aggregation. Additionally, the proposed methodology involves the creation of a dataset comprising images of boxes taken in warehouse settings. The proposed system is realized on the NVIDIA Jetson Nano platform, using an Arducam IMX477 camera. To evaluate the proposed model, we conducted experiments with our own dataset and compared the results with some state-of-the-art (SOTA) models. The proposed network achieved the highest detection accuracy with the fewest parameters compared to other SOTA models.

Fuzzy best–worst method–based approach for warehouse location selection and a case study in Izmir

PurposeThe study aims to propose a decision-support system to determine the location of a regional disaster logistics warehouse. Emphasizing the importance of disaster logistics, it considers the criteria to be evaluated for warehouse location selection. It is aimed to determine a warehouse location that will serve the disaster victims most efficiently in case of a disaster by making an application for the province of Izmir, where a massive earthquake hit in 2020.Design/methodology/approachThe paper proposes a fuzzy best–worst method to evaluate the alternative locations for the warehouse. The method considers the linguistic evaluations of the decision-makers and provides an advantage in terms of comparison consistency. The alternatives were identified through interviews and discussions with a group of experts in the fields of humanitarian aid and disaster relief operations. The group consists of academics and a vice-governor, who had worked in Izmir. The results of a previously conducted questionnaire were also used in determining these locations.FindingsIt is shown how the method will be applied to this problem, and the most effective location for the disaster logistics warehouse in Izmir has been determined.Originality/valueThis study contributes to disaster preparedness and brings a solution to the organization of the logistics services in Izmir.

Implementation of the AHP Method in Determining the Completion of Logistics Warehouse Stock Buildup Using the Expert Choice Application

The development of logistics services that are increasing has caused an increase in customers of PT. Astrans Putra Logistik also increased, this resulted in the logistics warehouse capacity experiencing a buildup of goods that almost filled the warehouse capacity which made operational activities disrupted, and many complaints from customers. Resolution to overcome this warehouse problem needs to be done so that the company’s operational efficiency is not disrupted and warehouse stock capacity becomes better. This study aims to find out the best solution of warehouse problems that occur through a decision making support system design using the AHP method assisted by the use of the Expert Choice 11 application. In making this decision, 4 stages are carried out, namely Intelligence, Design, Choice, and Analysis of Assessment Result which in the process have a 4 kinds of criteria and 4 kinds of alternative solutions. From the calculation of the AHP method assisted by the use of the Expert Choice 11 application, the weight of each criterion was obtained, namely Increased Operational Efficiency getting a weight of 0,259, Number of Items that can be Accommodated getting a weight of 0,086, Company Income getting a weight of 0,495, and Company Expense getting a weight of 0,160. From the calculation of alternative settlements, it was also found that The Addition of a New Departure Fleet got a weight of 0,385, The Construction of Branch Goods Warehouse got a weight of 0,279, Upgrading Small Trucks to Large Trucks got a weight of 0,187, and The Application of a Pre-order system for customers got a weight of 0,149.

Logistics warehousing system shelving station route planning based on X-ARM

The need for automated control in warehouse and logistics systems has increased recently, particularly in the area of cargo storage. The use of robot arms in manufacturing is an important area for development. Multi-arm actions, including switching between multiple arms, expand the number of potential operations that numerous operators can do, but they also bring more computing hurdles. Multiple robotic arm systems must operate with careful path planning. In this study, Based on previous research papers, we propose the utilization of dRRT* and mmdRRT* algorithms for efficient path planning. The dRRT* algorithm improves exploration and convergence to an ideal path by combining the advantages of the rapidly-exploring random tree (RRT) with the optimal RRT* algorithm. To address complicated and dynamic situations, the mmdRRT* algorithm, on the other hand, uses a multi-modal distribution model. We want to improve the reliability and effectiveness of path planning for various robotic arm systems by combining these two techniques.

Cognitive Enhancement of Robot Path Planning and Environmental Perception Based on Gmapping Algorithm Optimization

In the logistics warehouse environment, the autonomous navigation and environment perception of the logistics sorting robot are two key challenges. To deal with the complex obstacles and cargo layout in a warehouse, this study focuses on improving the robot perception and navigation system to achieve efficient path planning and safe motion control. For this purpose, a scheme based on an improved Gmapping algorithm is proposed to construct a high-precision map inside a warehouse through the efficient scanning and processing of environmental data by robots. While the improved algorithm effectively integrates sensor data with robot position information to realize the real-time modeling and analysis of warehouse environments. Consequently, the precise mapping results provide a reliable navigation basis for the robot, enabling it to make intelligent path planning and obstacle avoidance decisions in unknown or dynamic environments. The experimental results show that the robot using the improved Gmapping algorithm has high accuracy and robustness in identifying obstacles and an effectively reduced navigation error, thus improving the intelligence level and efficiency of logistics operations. The improved algorithm significantly enhances obstacle detection rates, increasing them by 4.05%. Simultaneously, it successfully reduces map size accuracy errors by 1.4% and angle accuracy errors by 0.5%. Additionally, the accuracy of the robot’s travel distance improves by 2.4%, and the mapping time is reduced by nine seconds. Significant progress has been made in achieving high-precision environmental perception and intelligent navigation, providing reliable technical support and solutions for autonomous operations in logistics warehouses.

Heuristics Integrated Deep Reinforcement Learning for Online 3D Bin Packing

Online 3D Bin Packing Problem (3D-BPP) has a wide range of industrial applications and there is an emerging research interest in learning optimal bin packing policy and deploying it for real logistics applications. From the heuristic methods to the deep reinforcement learning (DRL) methods, the previous works have proposed many solutions to solve the online 3D-BPP. However, none of them have studied what and how heuristics can be modelled into DRL to build a more effective and practical bin packing pipeline. In this work, we thoroughly investigate what heuristics can be used in online 3D-BPP and how to effectively integrate the heuristics with the DRL. First, we design 3 different heuristics based on the physical rules of the real world and the experiences of the human packers, including the Physics-Heuristics, the Packing-Heuristics and the Unpacking-Heuristics. Second, we model the 3 types of heuristics into the DRL framework and propose a novel heuristic DRL method to solve the online 3D-BPP. Extensive experimental results show that our method achieves state-of-the-art bin packing performance and the resulting real-world system is able to reliably finish the bin packing task in real logistics scenarios. Supplementary video is available at https://www.youtube.com/watch?v=x8GpmEELq18. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —The rapid growth of e-commerce has significantly increased the burden of human packers in logistic warehouses, where the workers need to pick the products from a conveyor and pack them into bins (i.e. the online 3D bin packing). Thus it is of great importance to develop intelligent robotic systems to replace human labor, which is a long-standing topic in the field of control and automation science. This paper makes a substantial contribution to the related field by studying the online 3D bin packing in terms of both the theory and practice. On the one hand, the simulated experiments suggest that the presented algorithm significantly improves the space utilization of bin packing. On the other hand, the robotic system developed based on the proposed method can favourably finish the bin packing task in real logistics scenarios, demonstrating the practical use of our approach. Consequently, the approach proposed in this paper is totally applicable in logistic warehouses and is promising to drastically improve the working efficiency of the product packing in real warehouses. In the future, we will extend the presented approach to pack irregular-shaped objects and then facilitate more logistics applications.

Оценка эффективности системы складирования международной компании при работе с маркетплейсами

Warehouse logistics, which is an independent field of knowledge, is of great im-portance as an element of logistic system. Warehousing problems arise and are solved at every stage of traffic of commodity and material flow. The company's warehousing system needs constant improvement and updating, especially under conditions of rapid technologi-cal development. Enterprises’ functioning is impossible without clear strategy of maintaining stock levels and coordinated resource storage system. Moreover, dynamic development of economic relations between expanding enterprises increases the need for warehouses, which provide acceptance, placement, accumulation and storage of material resources inventory, semi-finished products, and finished products.

Simulation modeling as a means of organizing technological processes in warehouse logistics

Simulation modeling as a means of organizing technological processes in warehouse logistics

МЕТОДЫ УПРАВЛЕНИЯ ТРАНСПОРТНЫМИ СИСТЕМАМИ НА ОСНОВЕ ВНЕДРЕНИЯ И ФУНКЦИОНИРОВАНИЯ ИНСТРУМЕНТОВ БЕРЕЖЛИВОГО ПРОИЗВОДСТВА НА ПРОМЫШЛЕННОМ ПРЕДПРИЯТИИ

In the current conditions of economic development, any industrial enterprise is working to increase the efficiency of its activities, in particular, by introducing logistical innovations into the production system that help reduce costs and increase output volumes. It is on this methodology that the logistics principles of «lean manufacturing» are based. In this paper, the concept of «lean manufacturing» is considered, which directly affects the reduction of losses, reduction of production costs and optimization of the main processes of warehouse logistics, and as a result, improving the quality of products, and also presents a model of the plan for creating a «lean warehouse».

Simulation and Optimization System of Automated E-Commerce Logistics Warehouse Allocation Network Based on Intelligent Algorithm

The prosperity of e-commerce has made our lives more convenient, but the logistics behind it has been silently paying. The e-commerce industry is expanding at an unprecedented rate, and with it comes explosive growth in logistics demand, especially in the warehouse distribution link. In order to meet this demand, the warehouse distribution system needs to be improved both in terms of technology and efficiency. This rapid development also brings a series of problems. First of all is the problem of logistics congestion. Due to the surge in orders, especially during peak shopping periods, logistics centers are often under great pressure. This not only affects the speed of delivery, but can also lead to damage or loss of goods. The purpose of this paper is to find an effective method to optimize the logistics warehouse allocation system of e-commerce, and to provide an efficient and reliable logistics optimization scheme for e-commerce enterprises. In this paper, data analysis and simulation methods are used to analyze. The experimental results show that PSO has the largest improvement in the order clerk operation efficiency (13%) and the smallest improvement in the order status (1%).

Comparative Analysis of Korean and Japanese Standards for Natural Smoke Ventilation in Logistic Warehouses

This study investigated the design methodologies outlined in Korean and Japanese legislation, along with Japanese design guidelines, pertaining to natural smoke ventilation systems in logistics warehouses. Subsequently, we determined the effective area of the smoke exhaust system based on the combustible materials and building characteristics. Our findings indicated that the calculated effective area per the statutory standards of both nations was 10 m&lt;sup&gt;2&lt;/sup&gt; and 20 m&lt;sup&gt;2&lt;/sup&gt;, respectively. According to Japanese guidelines, the space accommodating the CUP ranged from 24.71 m&lt;sup&gt;2&lt;/sup&gt; to 13.76 m&lt;sup&gt;2&lt;/sup&gt; for floor heights between 7 to 16 m, while the space accommodating CEP ranged from 41.83 m&lt;sup&gt;2&lt;/sup&gt; to 22.54 m&lt;sup&gt;2&lt;/sup&gt;. Analyzing the quantity of smoke emitted through the calculated effective area, we observed that, when applying domestic legal standards, the smoke exhaust rate consistently remained lower than the plume flow rate. Conversely, under the Japanese standard, the smoke emission efficiency of the CUP loading warehouse surpassed that of smoke emission from 9 m to 16 m, while it was lower from 7 m to 8 m. Notably, the smoke exhaust rate consistently exceeded the generated smoke quantity in all instances within the effective area governed by the guidelines.

Image Recognition Technology Applied to the Design of Mobile Platform for Warehouse Logistics Robots

Abstract This paper first studies the processing flow of image processing technology that preprocesses the image and adopts the method of polygonal approximation to identify the shape and localize the moving target. Then, the mobile platform of the warehouse logistics robot is designed. Then, the vision system of the robot was designed using image recognition technology to realize obstacle collision prediction and route planning. Finally, the robot’s localization and grasping abilities, trajectory following performance, and semantic segmentation abilities are analyzed using comparative experiments. The successful localization and grasping rates of the warehouse robots are all higher than 93%, and the trajectory following the straight line road section is better, with a maximum error of less than 21 mm. The mIoU of this paper’s method on the Cityscapes dataset is 78.85%, MPA is 86.05%, and PA is 96.89%, with good image segmentation performance. This study is of great significance for the development of the intelligent logistics field.

A multistart biased‐randomized algorithm for solving a three‐dimensional case picking problem with real‐life constraints

AbstractThis paper introduces the three‐dimensional case picking problem (3D‐CPP) and proposes a multistart biased‐randomized algorithm (BRA) to solve it. The 3D‐CPP combines two important topics in modern warehouse logistics: the pallet loading problem and the routing of pickers in manual warehouses. The proposed optimization procedure aims at minimizing the overall distance traveled by the pickers, and is achieved by combining a routing problem (i.e., the order in which picking positions are visited) with a loading problem (i.e., the way in which cases are placed onto the pallet). We also consider additional constraints regarding the weight, vertical support, and strength of the cases. In order to solve this problem, we first propose a constructive heuristic which combines routing and packing procedures. This initial heuristic is then extended into a multistart BRA by employing a skewed probability distribution to introduce a certain degree of randomness during the solution‐construction process. A series of computational experiments allow us to assess the quality of the proposed approach, through a comparison with other algorithms as well as using real‐life data provided by an industrial partner.

Mathematical modeling of mechatronic shuttles as automation objects for multilevel systems of intra-warehouse logistics

The subject of the study is the mathematical modeling of mechatronic shuttles of multilevel intra-warehouse logistics systems. The purpose of the article is to ensure energy efficiency and high productivity of multilevel warehouse logistics systems by developing mathematical models of mechatronic electromechanical drives as part of automated autonomous shuttle systems (Pallet Shuttle). To achieve this goal, it is necessary to solve the following tasks: to build a mathematical model of the processes occurring in the transportation shuttle as an electromechanical and mechatronic system; to build a mathematical model of the transportation shuttle as an automation object and to obtain a transfer function of the autonomous shuttle system for automatic control of its speed. Conclusions. The paper develops generalized approaches to the construction of mathematical models of electric drives as automation objects. The developed approach assumes that the linearized mathematical model of an electric drive as an automation object is represented as a linear differential equation with constant coefficients that relate the control and the controlled parameter. The construction of such a differential equation is proposed to be carried out by generalizing the properties inherent in electromechanical systems, and it is assumed that these properties are represented by Lagrange equations of the 2nd kind using electromechanical analogies. As a result of the research, it was shown that the use of this approach leads to a definite equation of the mathematical model of the mechatronic shuttle as an automation object. It is shown that the linearized mathematical model of the shuttle as an automation object should be determined by a differential equation of at least the second order. The research results prove the possibility of improving automation systems in design by taking into account the properties inherent in shuttles as electromechanical and mechatronic systems in more detail. It is shown that the use of this approach leads to a definite equation of the mathematical model of the mechatronic shuttle as an automation object, but it is generally almost impossible to obtain such an equation explicitly. To illustrate the proposed approach, we consider the modeling of a typical mechatronic electric drive of machines used in automated storages and present the results of modeling processes in the electric drive. It is shown that the linearized mathematical model of a mechatronic shuttle as an automation object should be determined by a differential equation of at least the second order. The research results show the possibility of improving automation systems during design due to a more detailed consideration of the properties inherent in shuttles as mechatronic electromechanical systems.

The concept of “Robot as a service” in warehousing logistics and prospects for its development in Russia

Aim. To present an overview of the “Robot as a Service” concept in the context of robotization, to conduct an analytical study in the process of comparing the traditional robotization model and RaaS model, as well as to assess the potential of a technology corporation in the development of RaaS solutions for various sectors and subjects of the economy.Objectives. To assess the dynamics of e-commerce, warehouse logistics and their interdependence through the prism of digital transformation; to investigate the evolutionary emergence of the business model “As a Service”, including in relation to robotization; to compare the traditional model of robotization and RaaS model in terms of advantages, limitations and potential business scenarios; to analyze the practical relevance of implementing RaaS solutions for small and medium-sized enterprises (SMEs) and non-technology corporations.Methods. The methodological basis of the study was the analysis of professional and academic literature. Empirical analysis, expressed in the assessment of practical relevance of RaaS-concept, was carried out on the basis of reported data on the projects implemented in the industry.Results. In the era of e-commerce, robotization of warehouse logistics shows significant potential to improve efficiency. The implementation of robotic solutions is a challenge due to the high initial investment, which becomes particularly sensitive for SMEs. The RaaS concept is evolutionary in nature and provides an opportunity to grow their business more proactively by robotizing warehouse processes, and offers prospects for a new business segment to technology corporations as a RaaS service provider.Conclusions. The RaaS model is more competitive than the traditional robotization model, especially in the context of SMEs and non-technological representatives of medium and large businesses. Technology corporations with their own robotization division can not only use their robots independently, but also develop as a RaaS service provider. Both SMEs and large businesses can be users of this service. The spread of robotization will have a significant impact on the level of innovative development and, as a consequence, on the efficiency of activities in general. The study confirms the relevance and prospects of the RaaS concept in the field of warehouse logistics, as well as suggests a potential provider of RaaS services in Russia.

Relocation of a warehouse for a cosmetic company: A case study

Warehouses are pivotal components within a company's supply chain, handling crucial functions such as receiving, storing, and delivering goods to end customers. While extensive research exists on the strategic location of warehouses in network optimization, there is a notable dearth of research on how to relocate a warehouse from one site to another, particularly while minimizing associated risks. This study sheds light on a low-risk approach undertaken by a multi-level marketing (MLM) company in Malaysia during the relocation of their warehouse. The study primarily addresses several key constraints: (i) Completion of the warehouse relocation exercise in 4.5 months; (ii) Termination of their warehouse staff services during the relocation; (iii) Elimination of disruption in the order fulfillment service level; (iv) Management of temperature-sensitive goods during the transfer and storage; (v) Seamless linkage between the third-party logistics (3PL) warehouse management system (WMS) and the company's systems. The primary objective of this study is to propose a resilient strategy for the relocation of their warehouse, taking into account these key constraints faced by the company.

INTEGRATION OF LOGISTICS FUNCTIONAL AREAS AND THE PLACE OF WAREHOUSING IN THEM

Warehousing logistics is a branch of logistics that deals with the development of effective methods for organizing warehousing, managing the procurement system, receiving, placing, accounting for inventory and inventory management in order to minimize costs associated with warehousing and processing of goods.As a complex technical structure, a warehouse consists of numerous interconnected elements, has a specific structure and performs the functions of transforming material flows, accumulating, processing and distributing goods among consumers. The possible variety of parameters, technological and space-planning solutions, designs of technological and handling equipment and characteristics of a diverse range of goods processed in warehouses classify warehouses as complex systems. At the same time, the warehouse itself is just an element of a higher-level system -the logistics chain, which forms the basic and technical requirements for the warehouse logistics subsystem, sets goals and criteria for its optimal functioning, and dictates the conditions for cargo processing.