Article
Economics
Xiaolong Guo, Ran Chen, Shaofu Du, Yugang Yu
Summary: This paper investigates replenishment operations in e-commerce warehouses and proposes a two-stage decomposition algorithm to optimize the storage of newly arrived items and reduce total travel distance. Numerical studies demonstrate that considering previously stored items can improve picking performance, and the algorithm significantly outperforms current policies in real-world applications.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2021)
Article
Computer Science, Artificial Intelligence
Veronika Lesch, Patrick B. M. Mueller, Moritz Kraemer, Marius Hadry, Samuel Kounev, Christian Krupitzer
Summary: Order picking is a labor-intensive and costly task in warehouses, with employees playing a major role in warehouse performance. Existing approaches focus on optimizing economic criteria but fail to address ergonomic criteria and the interdependence of storage assignment and order picking problems. In this study, we propose customized versions of NSGA-II and ACO algorithms that simultaneously consider economic and ergonomic constraints and incorporate knowledge about the interdependence between the two problems. Evaluation results show that our proposed algorithms outperform commonly used techniques in terms of quality indicators and the combination of both algorithms results in better performance.
APPLIED INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
K. L. Keung, C. K. M. Lee, P. Ji
Summary: This paper investigates the value of utilizing Industrial Internet of Things (IIoT)-driven robotic mobile fulfillment system for enhancing operational efficiency in resource synchronization and information transfer. The study compares different algorithms and storage assignment rules to minimize operation costs.
ADVANCED ENGINEERING INFORMATICS
(2022)
Review
Chemistry, Multidisciplinary
Amir Reza Ahmadi Keshavarz, Davood Jaafari, Mehran Khalaj, Parshang Dokouhaki
Summary: The study examines the combination of multiple order-picking planning problems, aiming to reduce logistics costs and improve customer satisfaction in competitive markets. Effective warehouse management and implementation of order-picking systems are essential to enhance production efficiency and maintain customer satisfaction.
APPLIED SCIENCES-BASEL
(2021)
Article
Engineering, Industrial
Ruben D'Haen, Kris Braekers, Katrien Ramaekers
Summary: This study proposes an integrated solution approach to handle dynamic order arrivals in warehouses and emphasizes the importance of anticipating future order arrivals to maintain high customer service levels. A new large neighbourhood search algorithm is developed to solve the online, integrated batching, routing and scheduling problem, outperforming the current state-of-the-art static solution algorithm. Experimental results provide insights on the particularity of this online, integrated problem, enabling companies to operate efficiently without compromising customer satisfaction.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Serhat Saylam, Melih Celik, Haldun Sural
Summary: This paper investigates the order picker routing problem in a dynamic and synchronised zoning environment, aiming to minimize the maximum time of completing picking activities in any zone. The use of a min-max type objective helps balance the workload of order pickers more effectively.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Sarah Vanheusden, Teun van Gils, Kris Braekers, Katrien Ramaekers, An Caris
Summary: Intensified competition leads to warehouses handling more orders in shorter timeframes, challenging timely retrieval of customer orders. Balancing workload to reduce imbalances can improve the stability of order picking operations. Various workload balancing methods have differing effectiveness, with managerial decisions impacting the choice of measure.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Management
Jelmer Pier van der Gaast, Felix Weidinger
Summary: This paper presents a novel strategic decision support framework for the design of an order picking system, which allows for the comparison of different systems and control mechanisms in a given customer order structure. By utilizing recent advancements in deep neural networks, the framework provides an efficient methodology for selecting the best order picking system and design parameters. It enables warehouse companies to objectively compare a large number of systems and identify the most promising order picking systems.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Jingran Liang, Zhengning Wu, Chenye Zhu, Zhi-Hai Zhang
Summary: The rapid growth of E-commerce sales has brought opportunities and challenges to warehouses, and adopting the Wave-Picking strategy can effectively address these issues. This research establishes a mixed integer mathematical model based on the characteristics of a Wave-Picking warehouse and develops a set of effective algorithms to solve the load-assignment and picker-routing problems.
JOURNAL OF INTELLIGENT MANUFACTURING
(2022)
Article
Engineering, Manufacturing
Kazunori Maruyama, Takashi Yamazaki
Summary: This study proposes a co-optimization method using order batching and storage location assignment to improve the efficiency of order picking in stock-type warehouses at production sites and supply chains. The numerical experiments validate the effectiveness and efficiency of the co-optimization method in controlling and executing local optimization techniques based on order characteristics.
JOURNAL OF ADVANCED MECHANICAL DESIGN SYSTEMS AND MANUFACTURING
(2022)
Article
Engineering, Industrial
Wei Jiang, Jiyin Liu, Yun Dong, Li Wang
Summary: With the rapid development of e-commerce, B2C warehouses are facing the challenge of processing heterogeneous and small volume orders. Traditional storage strategies are no longer advantageous, leading to the exploration of scattered storage strategies. A new scattered storage strategy considering product correlation, formulated as a 0-1 integer programming model, was proposed in this study. GA and basic PSO algorithms were developed for large-scale problem solving, with a specially designed new PSO algorithm and a hybrid algorithm showing improved solution quality.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Materials Science, Multidisciplinary
Findan Block, Finn Klingbeil, Umer Sajjad, Christine Arndt, Sandra Sindt, Dennis Seidler, Lars Thormaehlen, Christine Selhuber-Unkel, Jeffrey McCord
Summary: Controlled transport of cells in biomedical applications can be achieved by designing soft magnetic elements to form a transport network using computational methods. This enables precise cell location and manipulation on surfaces using rotational magnetic fields. The networks allow for variable movement patterns of magnetic carriers and cells and can be integrated with CMOS-compatible materials.
ADVANCED MATERIALS TECHNOLOGIES
(2023)
Article
Computer Science, Interdisciplinary Applications
S. G. Ozden, A. E. Smith, K. R. Gue
Summary: This paper presents an open-source computational software system for designing warehouse layouts to minimize the average walking distance for pickers, by automatically generating and evaluating various design options to approach near-optimality.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Environmental Sciences
Changwan Han, Hyeongjun Jeon, Junghyun Oh, Heungjae Lee
Summary: This study aims to assign real-time received orders to multiple UAVs in the warehouse using the modified interventionist method and dynamic path planning, and determine the picking sequence and path for each UAV. A halting and correcting strategy is proposed to consider the similarity between the UAV's picking list and the orders. The results show that the proposed method reduces completion time, UAV's travel distance, and collapsed time compared to the previous algorithm.
Review
Engineering, Industrial
Thomas De Lombaert, Kris Braekers, Rene De Koster, Katrien Ramaekers
Summary: Efficient order picking system is crucial for high-performing warehouses and human operators will continue to play a significant role. However, current planning models only partly consider the specific skills, conduct, and perceptions of human operators. This review adopts a multimethod approach to identify and analyze how these phenomena are integrated into order picking planning problems and provides recommendations for refining human factors integration constructs.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
