Article
Computer Science, Interdisciplinary Applications
Maximilian Loffler, Nils Boysen, Michael Schneider
Summary: This paper investigates the routing algorithms for AGV-assisted order picking in parallel-aisle warehouses. It proposes a dynamic programming routine with polynomial runtime for fixed picking order sequences and offers a heuristic for cases where order sequencing is a decision. The use of AGVs has shown to significantly improve order-fulfillment processes in warehouses.
INFORMS JOURNAL ON COMPUTING
(2022)
Review
Management
Nils Boysen, Stefan Schwerdfeger, Konrad Stephan
Summary: This paper explores the synchronization problems that arise in warehouses that have evolved into fully-automated fulfillment factories due to the success of e-commerce. By optimizing workstation setups and implementing synchronization operations, the picking efficiency can be improved and the burden on the bin supply system can be reduced. The findings demonstrate that the right workstation setup significantly enhances throughput performance.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Engineering, Industrial
Alexandros Pasparakis, Jelle De Vries, Rene De Koster
Summary: Robotisation is becoming more common in warehouse operations, but human employment remains relevant. The traditional manual activities are being transformed into collaborative human-robot tasks, reflecting the shift towards a human-centric Industry 5.0. However, the recruitment and retention of human workers are becoming increasingly challenging. This research investigates the sustainable deployment of robotic technologies alongside human workers, examining the impact of autonomy levels on job satisfaction and core self-evaluations, which determine turnover intentions. The findings reveal that human-robot collaboration has a positive effect on job satisfaction, particularly when the human is following the robot, and it also enhances pickers' self-esteem and self-efficacy related to human-robot interaction.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Vivek Vijayakumar, Ahmad Sobhani
Summary: Picker to parts order picking (OP) systems are labor-intensive and costly in the e-commerce industry, accounting for 55% of warehouse expenses. To improve working conditions, the automated OP system should focus on Industry 5.0 principles and integrate with human workers. Pick and transport robots (PTRs) are a compatible solution for the OP system. However, there is limited research on the human factor effects of using PTRs in optimizing system performance. This research develops a mathematical model to optimize the performance of a picker to parts OP system using PTRs in terms of productivity, quality, and well-being of order pickers.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Economics
Suryakant Kumar, Jiuh-Biing Sheu, Tanmoy Kundu
Summary: This study investigates the planning issue of robot-human coordination in e-commerce warehousing using a queueing theory based analytical model. The critical planning decisions include determining the optimal number of robots, the expected number of robots at essential locations, and analyzing the performance of the order picking system. The study introduces the concept of perceived workload, which depends on the number of robots, to design an efficient order fulfillment model. The findings suggest a trade-off between deploying more robots and the warehousing system's performance, as well as the significant impact of workload-dependent service rate on robot queueing in the warehouse.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2023)
Article
Management
Arsham Atashi Khoei, Haldun Sural, Mustafa Kemal Tural
Summary: This paper introduces the energy minimizing order picker forklift routing problem (EMFRP) in the context of warehouse operations. It aims to find an energy-efficient route for order picker forklifts to pick a given list of items, which can significantly reduce energy consumption and CO2 emission. The study proposes mathematical formulations, dynamic programming approaches, and heuristic algorithms to solve the EMFRP and achieve high-quality solutions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Sven Winkelhaus, Minqi Zhang, Eric H. Grosse, Christoph H. Glock
Summary: Order picking is a critical process that affects business success in various industries. While manual operations are still common, there are also technologies available to automate or support order picking. This study examines hybrid order picking, where autonomous robots and human pickers work together, and evaluates its performance using a simulation model. The results show that hybrid order picking can improve throughput and reduce costs compared to pure manual or automated order picking. Future research potentials are discussed based on the simulation results.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Review
Engineering, Industrial
Marc Fuchtenhans, Eric H. Grosse, Christoph H. Glock
Summary: Smart lighting systems have been widely discussed in the literature, but their potentials in industrial environments have been rarely addressed. Industrial environments have different requirements for lighting systems, and this paper explores the application potential of smart lighting systems in improving warehouse order picking efficiency.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Economics
Masoud Mirzaei, Nima Zaerpour, Rene de Koster
Summary: Order picking is a demanding activity in many warehouses, with storage assignment policies playing a crucial role in efficiency. By considering product affinity, warehouses can make informed decisions to reduce retrieval time and improve efficiency.
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
(2021)
Article
Mathematics
Kaibo Liang, Li Zhou, Jianglong Yang, Huwei Liu, Yakun Li, Fengmei Jing, Man Shan, Jin Yang
Summary: This paper presents a study on the order-picking process in a distribution center, employing a parts-to-picker system, based on dynamic order batching and task optimization. It proposes a new method of the hybrid time window and establishes an order consolidation batch strategy to minimize the number of target shelves for picking. A heuristic algorithm is designed to select a shelf selection model, and an improved ant colony algorithm is used to solve the AGV task allocation problem. The paper also proposes methods to optimize static picking station selection and dynamically select picking stations based on the queuing situation.
Article
Computer Science, Artificial Intelligence
Giulia Pugliese, Xiaochen Chou, Dominic Loske, Matthias Klumpp, Roberto Montemanni
Summary: This study focuses on a hybrid picker-to-parts order picking system, where human operators collaborate with Automated Mobile Robots (AMRs), presenting new mathematical models for optimization and synchronization of picking operations experimentally evaluating alternative implementations for the AMR system.
Article
Engineering, Industrial
Ibrahim Muter, Temel Oncan
Summary: This article focuses on the integration of order batching and picker scheduling decisions, proposing a column generation-based exact algorithm to efficiently solve this challenging optimization problem. Experimental results demonstrate that the proposed algorithms are capable of solving instances with up to 100 orders.
Article
Management
Ivan Zulj, Hagen Salewski, Dominik Goeke, Michael Schneider
Summary: The study focuses on an AMR-assisted picker-to-parts system in warehouses, aiming to minimize the total tardiness of customer orders by partitioning the warehouse into zones, using AMRs to support order pickers, and optimizing the travel and walking speed ratios between AMRs and order pickers. Increasing the speed ratio is found to be more effective in reducing total tardiness compared to increasing the AMR fleet size.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Management
Yanling Zhuang, Yun Zhou, Yufei Yuan, Xiangpei Hu, Elkafi Hassini
Summary: This paper studies an automated warehousing system that uses robots to move racks to multiple workstations, enabling pickers to retrieve products from the racks for order fulfillment. The paper addresses the challenge of considering order and rack sequences simultaneously, while also ensuring workload balance and resolving rack conflicts among the workstations. To solve this problem, a comprehensive mixed integer programming model is formulated, and an adaptive large neighborhood search method is proposed. The proposed approach demonstrates significant improvements in rack movements compared to existing practices, with potential savings of up to 62% in a real-world dataset.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2022)
Article
Mathematics
Shandong Mou
Summary: Studied the integrated Order Picking and Heterogeneous Picker Scheduling Problem in omni-channel retail stores, designed a hybrid heuristic algorithm to solve the problem, and validated its performance and the impact of factors.
Article
Management
Marc Fuechtenhans, Christoph H. Glock, Eric H. Grosse, Simone Zanoni
Summary: This paper presents a simulation model for evaluating the cost benefits of using smart lighting systems in warehouses. The results of the model indicate that smart lighting systems have great potential for reducing energy consumption and improving environmental footprints compared to conventional lighting systems.
INTERNATIONAL JOURNAL OF LOGISTICS-RESEARCH AND APPLICATIONS
(2023)
Article
Management
Heiko Diefenbach, Nathalie Erlemann, Alexander Lunin, Eric H. Grosse, Kai-Oliver Schocke, Christoph H. Glock
Summary: This paper examines the issues and countermeasures in the air freight supply chain from both economic and ergonomic perspectives. It suggests digitalization of processes and improvement of ergonomic conditions for workers as means to address the problems.
INTERNATIONAL JOURNAL OF LOGISTICS-RESEARCH AND APPLICATIONS
(2023)
Article
Engineering, Industrial
Azin Setayesh, Eric H. Grosse, Christoph H. Glock, W. Patrick Neumann
Summary: Through literature review and interviews, this study identified human factors leading to quality deficits and errors in order picking operations, including physical and mental fatigue, complexity, memory demand, among others. The interviews also revealed previously unrecognized communication and supervision failure modes.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Management
Heiko Diefenbach, Simon Emde, Christoph H. Glock
Summary: This paper addresses the electric vehicle scheduling problem in an in-plant logistics setting with multiple charging stations. It introduces an integer programming model and a branch-and-check solution procedure to minimize the required fleet size. The study considers different battery charging functions and shows that the branch-and-check approach outperforms the standard solver in terms of computational efficiency.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Review
Computer Science, Interdisciplinary Applications
Frederic Jacob, Eric H. Grosse, Stefan Morana, Cornelius J. Koenig
Summary: The industrial application of collaborative robots in warehouses is driven by factors such as just-in-time delivery, shorter product life cycles, demographic changes, and the Covid-19 pandemic. These robots work alongside human workers, increasing productivity and relieving them of repetitive or strenuous tasks. However, acceptance of human-robot collaboration (HRC) in warehouses can be hindered by concerns such as job loss, stress, effort, and risk to physical integrity. This study analyzes HRC acceptance in warehouses using the Unified Theory of Acceptance and Use of Technology, identifying key factors and providing guidance for future research and managers regarding HRC applicability.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Engineering, Industrial
Minqi Zhang, Eric H. Grosse, Christoph H. Glock
Summary: Warehouses are crucial in supply chains, and order picking is a time- and cost-intensive task. New technologies, such as autonomous picking robots collaborating with human pickers, can reduce the workload of warehouse workers. However, attention should be given to controlling the weight handled by pickers to avoid increased ergonomic risks.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2023)
Article
Engineering, Industrial
Azin Setayesh, Eric H. Grosse, Michael A. Greig, Christoph H. Glock, W. Patrick Neumann
Summary: This paper evaluates the usability, functionality, and usefulness of the Warehouse Error Prevention (WEP) tool, which consists of seven modules. The WEP tool, designed in a simple yes/no form, aims to identify human factors associated with pick errors in warehouses. The tool was tested and evaluated by 33 participants from 27 organizations in three different countries. Survey results indicate that the participants found the WEP tool to be usable and functional. In interviews, participants reported the tool as accurate and effective, with the potential to improve order picking quality for engineers, ergonomists, and warehouse managers. Further quantitative field testing is required to assess the WEP tool's ability to identify costly warehouse errors.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Marc Fuechtenhans, Christoph H. Glock
Summary: This paper investigates the issue of energy demand and renewable energy usage increase in the manufacturing industry, and explores how production and energy supply can be coordinated through incentive-based programs and energy-efficient scheduling models. A bi-objective job-shop scheduling problem with variable machine speeds is solved using a genetic algorithm, and Pareto frontiers are derived to analyze the trade-off between total energy consumption and total weighted tardiness.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Editorial Material
Engineering, Industrial
Eric H. Grosse, Fabio Sgarbossa, Cecilia Berlin, W. Patrick Neumann
Summary: Industry 4.0 focused on performance and profit, but failed to address the prosperity of all stakeholders, leading to the introduction of Industry 5.0. Industry 5.0 is a human-centric approach that emphasizes outcomes for humans and promotes the development of resilient and sustainable systems.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Davide Castellano, Mose Gallo, Christoph H. Glock
Summary: This paper investigates a single-vendor, multiple-buyer coordinated supply chain under stochastic demand. The problem is finding the production and inventory replenishment policy, production rate, and lead times that minimize the long-run expected total cost per time unit. An optimization algorithm is developed and its performance is compared to a benchmark algorithm based on a commercial solver in a numerical experiment. The experiments also investigate the benefits stemming from the proposed model when compared to models reproducing situations that leverage some or any of the controlled factors.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Proceedings Paper
Automation & Control Systems
Steffen Nixdorf, Minqi Zhang, Fazel Ansari, Eric H. Grosse
Summary: The integration of AI technologies and learnable systems in production and logistics transforms the concepts of work organization and task assignments. Intelligent machines and human workers can guide and train each other in the workplace to cope with emerging skill mismatches. The concept of Reciprocal Learning (RL) between humans and intelligent machines has emerged, but the literature on this topic is fragmented, especially in production and logistics. This paper aims to conduct a systematic literature review to develop a comprehensive knowledge base on RL and contribute to future research on human-machine symbiosis in production and logistics.
Proceedings Paper
Automation & Control Systems
Minqi Zhang, Eric H. Grosse, Christoph H. Glock
Summary: With the increasing market penetration of smart devices, mobile applications have become essential tools in daily life and industrial work. However, the limitations of smart devices require validation experiments to ensure the reliability of app usage, and more research is needed on the psychosocial aspects of human-technology interaction.
Article
Engineering, Industrial
Hiroshi Matsuhisa, Nobuo Matsubayashi
Summary: This study investigates the formation of an alliance between competing manufacturers and a monopolistic platform retailer, and analyzes the impact of the degree of differentiation among manufacturers on the formation of the alliance and the profitability of the retailer.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Article
Engineering, Industrial
Lingxuan Kong, Ge Zheng, Alexandra Brintrup
Summary: Supply Chain Financing is used to optimize cash flows in supply networks, but recent scandals have shown inefficiencies in risk evaluation. This paper proposes a Federated Learning framework to address order-level risk evaluation.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Article
Engineering, Industrial
Jing Gu, Xinyu Shi, Junyao Wang, Xun Xu
Summary: The asymmetric market power between a firm and its partners negatively affects the firm's financial performance. Building relationships with suppliers or customers that have matched market power is the best approach. The strength of the buyer-supplier relationship amplifies the negative impact of asymmetric market power, while the level of relationship embeddedness reduces its negative effect. Moreover, firm-specific institutional, industry, and regional economic heterogeneities also influence the financial impact of asymmetric market power.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Article
Engineering, Industrial
Yu Du, Jun-qing Li
Summary: This study investigates the group scheduling of a distributed flexible job shop problem using the concrete precast process. The proposed solution utilizes three coordinated double deep Q-networks (DQN) as a learn-to-improve reinforcement learning approach. The algorithm shows superiority in minimizing costs and energy consumption.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Article
Engineering, Industrial
Xiaoyu Yan, Weihua Liu, Ou Tang, Jiahe Hou
Summary: This study analyzes the market amplification effect and the impact of entrant's overconfidence on a two-sided platform. The results show that overconfident entrants can lead to price increases and benefit both the existing firms and themselves to a certain extent.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Article
Engineering, Industrial
Illya Kaynov, Marijn van Knippenberg, Vlado Menkovski, Albert van Breemen, Willem van Jaarsveld
Summary: The One-Warehouse Multi-Retailer (OWMR) system is a typical distribution and inventory system. Previous research has focused on heuristic reordering and allocation strategies, which are time-consuming and problem-specific. This paper proposes a Deep Reinforcement Learning (DRL) algorithm for OWMR problems, which infers a multi-discrete action distribution and improves performance with a random rationing policy.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Article
Engineering, Industrial
Yimeng Sun, Ruozhen Qiu, Minghe Sun
Summary: This study considers a multi-period inventory management problem for a retailer offering limited-time discounts and having a joint service-level requirement under demand uncertainty. It proposes a double-layer iterative approach to solve the problem and maximize total profit while balancing the service level using a posteriori method and an affinely adjustable robust chance-constrained model.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Article
Engineering, Industrial
Anas Neumann, Adnene Hajji, Monia Rekik, Robert Pellerin
Summary: This paper presents a new mathematical formulation for planning and scheduling activities of Engineer-To-Order (ETO) projects, along with a new ETO strategy to reduce the impacts of design uncertainty. The study proposes a hybrid Layered Genetic Algorithm combined with an adaptive Lamarckian learning process (LLGA) and compares it with the branch-and-cut procedure of CPLEX. The results show good performance of the proposed mathematical model for small and medium-sized instances.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Article
Engineering, Industrial
Thilini Ranasinghe, Chanaka D. Senanayake, Eric H. Grosse
Summary: Production systems are undergoing transformative changes, necessitating adaptability from human workers. This study developed an analytical model to account for stochastic processing times and learning heterogeneity, revealing insights into system performance.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Article
Engineering, Industrial
Sunil Tiwari, Pankaj Sharma, Ashish Kumar Jha
Summary: Black Swan events such as the COVID-19 pandemic and the Suez Canal blockage have a significant impact on firms' technology adoption decisions, especially in terms of disruptions and digitalization in the supply chains. This study investigates the influence of institutional forces and environmental contingencies on supply chain digitalization from an institutional and contingency theory perspective. The findings emphasize the importance of organizational readiness and people readiness, including top management involvement and employee training, in facilitating digitalization.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Article
Engineering, Industrial
Fabio Neves-Moreira, Pedro Amorim
Summary: Omnichannel retailers are using stores as distribution centers to provide faster online order fulfillment services. However, in-store picking operations can impact the offline customer experience. To address this, we propose a Dynamic In-store Picker Routing Problem (diPRP) that minimizes customer encounters while fulfilling online orders. Our solution approach combines mathematical programming and reinforcement learning to find efficient picking policies that reduce customer encounters.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Article
Engineering, Industrial
Richard Kraude, Ram Narasimhan
Summary: In this study, the relationship between Vertical Integration (VI) and Environmental Performance (EP) is examined, revealing that highly integrated firms produce less waste but engage in fewer environmental initiatives. These findings are crucial for understanding the impact of stakeholder exposure on organizational behavior.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)
Review
Engineering, Industrial
Korina Katsaliaki, Sameer Kumar, Vasilis Loulos
Summary: This research conducts a systematic literature review (SLR) and content analysis on Supply Chain Coopetition (SCC) through the PRISMA framework. It examines the theory of coopetition and organizational relationships in intra-firm and inter-firm supply chains, focusing on collaboration between rival manufacturers. The study identifies structures and mechanisms of coopetition, such as buyer-supplier coopetition, supply networks coopetition, and production and distribution/logistics coopetition. It provides a holistic approach to SCC management practices and serves as a guide for future research.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2024)