Article
Chemistry, Multidisciplinary
Chirag Chandrashekar, Pradeep Krishnadoss, Vijayakumar Kedalu Poornachary, Balasundaram Ananthakrishnan, Kumar Rangasamy
Summary: With the advancement of technology and time, various algorithms have been proposed to improve the performance of individual units or structures used in the cloud environment. Task scheduling is one of the most important sections of cloud computing, responsible for optimizing the time taken to execute processes and improving efficiency. This paper proposes an ideal and optimal task scheduling algorithm and compares it with other existing algorithms in terms of efficiency, makespan, and cost parameters.
APPLIED SCIENCES-BASEL
(2023)
Article
Automation & Control Systems
Weishi Shao, Zhongshi Shao, Dechang Pi
Summary: This article studies a distributed heterogeneous hybrid flow shop scheduling problem and proposes an ACO_MOEA/D algorithm for solving the problem, which considers the optimization objectives from the view of production and management and is validated through various experiments for its efficiency and effectiveness.
IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING
(2022)
Article
Computer Science, Information Systems
Cunli Song
Summary: This study investigates an energy-oriented scheduling problem derived from a hybrid flow shop with unrelated parallel machines. A hybrid multi-objective teaching-learning based optimization algorithm is proposed, which effectively reduces standby and turning on/off energy consumption, improves algorithm convergence speed, and enhances exploration and exploitation capabilities. Experimental results across 15 cases verify the effectiveness and superiority of the proposed algorithm.
Article
Computer Science, Interdisciplinary Applications
Zeynep Adak, Mahmure Ovul Arioglu, Serol Bulkan
Summary: The paper addresses the scheduling problem of multiprocessor open shop, which is strongly NP-hard. By introducing a novel efficient solution representation and ant colony optimization model, an effective algorithm is proposed and outperforms the current state-of-the-art algorithm on 100 benchmark instances.
JOURNAL OF COMBINATORIAL OPTIMIZATION
(2022)
Article
Automation & Control Systems
Serap Ercan Comert, Harun Resit Yazgan
Summary: This paper introduces three multi-objective electric vehicle routing problems that consider different charging strategies and electric vehicle charger types while optimizing five conflicting objectives. A new hierarchical approach consisting of Hybrid Ant Colony Optimization (HACO) and Artificial Bee Colony Algorithm (ABCA) is developed to solve these problems. The proposed approach is examined on test-based instances and achieves the best new results in most cases.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Review
Management
Janis S. Neufeld, Sven Schulz, Udo Buscher
Summary: This article presents the research progress on multi-objective hybrid flow shop scheduling problems, identifies important features in optimization algorithms, and provides a framework and test instances for evaluating algorithm suitability. The article is of great theoretical and practical significance for solving multi-objective optimization problems.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Mohamed Kurdi
Summary: This work proposes a new metaheuristic algorithm called ACONEH for open shop scheduling problem with the goal of improving the exploration capability of ant colony optimization and solving OSSP more effectively. The algorithm utilizes a new heuristic information approach that incorporates randomness, diversity, and improvability. Experimental results show that ACONEH achieves significant improvements in reducing the makespan of OSSP compared to traditional methods.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Weishi Shao, Zhongshi Shao, Dechang Pi
Summary: This paper studies a multiobjective distributed hybrid flow shop scheduling problem (MDHFSP) and proposes a multi-objective evolutionary algorithm to solve it, optimizing solutions effectively through multiple neighborhoods local search operators and an adaptive weight updating mechanism.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Hernan Diaz, Juan J. Palacios, Ines Gonzalez-Rodriguez, Camino R. Vela
Summary: In this paper, a new Artificial Bee Colony algorithm is proposed to solve a variant of the Job Shop Scheduling Problem with uncertain processing times. The algorithm incorporates a diversification strategy based on the seasonal behavior of bees to avoid premature convergence. A thorough parametric analysis and comparison of different seasonal models are conducted, showing the improved performance of the proposed algorithm. Additionally, an assessment of the solutions' robustness under different ranking operators and a sensitivity analysis on the effect of uncertainty levels are performed.
INTEGRATED COMPUTER-AIDED ENGINEERING
(2023)
Article
Mathematics
Mei Li, Gai-Ge Wang, Helong Yu
Summary: This paper studies the fuzzy hybrid green shop scheduling problem with fuzzy processing time, aiming to minimize makespan and total energy consumption. By proposing a discrete artificial bee colony algorithm, it achieves higher diversity and convergence speed.
Article
Computer Science, Artificial Intelligence
Yan Wang, Zhao-hong Jia, Xing-yi Zhang
Summary: This study addresses a multi-stage flexible flow shop scheduling problem with batch processing machines, aiming to minimize the makespan and total energy consumption. A hybrid meta-heuristic algorithm based on ant colony optimization and genetic algorithms is proposed to solve the problem, with extensive simulation experiments conducted to verify its effectiveness and efficiency.
SWARM AND EVOLUTIONARY COMPUTATION
(2022)
Article
Multidisciplinary Sciences
Jingcao Cai, Shejie Lu, Jun Cheng, Lei Wang, Yin Gao, Tielong Tan
Summary: This study investigates the distributed scheduling problem in hybrid flow shops and proposes a collaborative variable neighborhood search algorithm (CVNS) to simultaneously minimize total tardiness and makespan. The algorithm simplifies the problem and defines various neighborhood structures and global search operators. Experimental results validate the advantages of CVNS over the considered problem.
SCIENTIFIC REPORTS
(2022)
Article
Computer Science, Information Systems
Sudheer Mangalampalli, Ganesh Reddy Karri, Mohit Kumar
Summary: The scheduling of applications in cloud computing is a significant challenge, and efficient algorithms are needed to handle diverse workloads and improve performance metrics. This study proposes a nature inspired multi-objective task scheduling Grey wolf optimization (MOTSGWO) algorithm that makes scheduling decisions based on the status of cloud resources and upcoming workload demands. The proposed technique outperforms other baseline policies and improves significant parameters.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Youjun An, Xiaohui Chen, Yinghe Li, Yaoyao Han, Ji Zhang, Haohao Shi
Summary: With the proposal of an improved non-dominated sorting biogeography-based optimization (INSBBO) algorithm, this paper aims to solve the (hybrid) multi objective flexible job-shop scheduling problem. By introducing the V-dominance principle, HVNS structure and ESS strategy, the algorithm's performance has been enhanced and shows better performance compared to other intelligent algorithms.
APPLIED SOFT COMPUTING
(2021)
Article
Automation & Control Systems
Hanxiao Li, Kaizhou Gao, Pei-Yong Duan, Jun-Qing Li, Le Zhang
Summary: This work proposes an improved artificial bee colony algorithm with Q-learning, named QABC, for solving the permutation flow-shop scheduling problem. Experimental results demonstrate the superiority of QABC over other algorithms in solving the concerned problems.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Management
Xin Wang, George Q. Huang
Summary: The booming parcel shipping business has attracted wide attention, with the trunk line being easier to manage but the first mile facing challenges of high empty haul rates and low efficiency. This paper explores a new business model of establishing a common service platform for the first mile and investigates strategic decisions of courier logistics companies in a competitive market. Results show that cooperation with the platform can lead to profit increases for companies and price decreases for customers, but companies running two channels may suffer profit losses under intense internal competition.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Daqiang Guo, Mingxing Li, Ray Zhong, G. Q. Huang
Summary: This paper introduces an Industry 4.0 paradigm-GiMS, which aims to explore Industry 4.0 technologies opportunities on operations and production management, especially on production planning, scheduling, execution and control.
INDUSTRIAL MANAGEMENT & DATA SYSTEMS
(2021)
Article
Engineering, Industrial
Mengdi Zhang, Saurabh Pratap, Zhiheng Zhao, D. Prajapati, George Q. Huang
Summary: This research addresses a vehicle routing problem with simultaneous pickup and delivery with time windows from multiple depots in the B2C e-commerce logistics system. By developing a mixed-integer non-linear programming model and using exact optimization methods and metaheuristic algorithms, the study successfully minimizes transportation costs and penalties in large-scale instances.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Ming Li, Saijun Shao, Qiwen Ye, Gangyan Xu, George Q. Huang
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2020)
Article
Computer Science, Interdisciplinary Applications
Arjun Rachana Harish, X. L. Liu, Ray Y. Zhong, George Q. Huang
Summary: This study aims to utilize digital assets to support logistics financing and introduces a logistics financing platform, Log-Flock, leveraging IoT, CPS, and blockchain technologies. The platform is expected to significantly reduce financing time and communicate the operational capabilities of logistics companies through credit ratings, making it easier for financing institutions to understand.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Mingxing Li, Ray Y. Zhong, Ting Qu, George Q. Huang
Summary: Cyber-physical systems (CPS) hold great potential in smart manufacturing, but the complexity and uncertainty of manufacturing optimization remain a challenge. This paper introduces a novel divide and conquer approach, Spatial-Temporal Out-Of-Order execution (ST-OOO), to decompose the complex optimization problem into smaller subproblems and generate a global solution through rolling spatiotemporal execution.
JOURNAL OF INTELLIGENT MANUFACTURING
(2022)
Article
Computer Science, Interdisciplinary Applications
Zhiheng Zhao, Leidi Shen, Chen Yang, Wei Wu, Mengdi Zhang, George Q. Huang
Summary: Modern warehousing systems for fresh and cold-keeping storage have complex operation procedures, accelerated pace, and high labour intensity, leading to hazardous working environments. This paper introduces an IoT and digital twin-enabled tracking solution framework for safety management, with an indoor safety tracking mechanism developed for real-time precise location information. A case study demonstrates the feasibility and effectiveness of the proposed techniques, showing high accuracy in detecting abnormal behavior and ensuring long-term use through adaptation.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Article
Computer Science, Interdisciplinary Applications
Zhiheng Zhao, Ray Y. Zhong, Yong-Hong Kuo, Yelin Fu, G. Q. Huang
Summary: iGather is a novel cyber-physical architecture for spatial temporal analytics that traces COVID-19 indirect contacts through digital chromosomes, representing human activity instances in the physical world. The deployment of physical hardware and spatial temporal analytics has shown high spatial temporal correlation and indirect tracing capabilities, confirmed through testing in various spatial temporal correlated cases.
INDUSTRIAL MANAGEMENT & DATA SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Chen Yang, Shulin Lan, Tingyu Lin, Lihui Wang, Zilong Zhuang, George Q. Huang
Summary: Hong Kong's warehousing industry is undergoing a transformation towards automation and efficiency driven by e-commerce growth and regional competition. A new business model incorporating a warehousing equipment supplier as a third party is proposed to address the lack of technical capability and motivation among stakeholders. Cooperative game theory is used to analyze profit distribution, essential conditions for success, and factors affecting efficiency in the new model.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2021)
Article
Computer Science, Interdisciplinary Applications
Yishuo Jiang, Xinlai Liu, Kai Kang, Zicheng Wang, Ray Y. Zhong, George Q. Huang
Summary: Modular Integrated Construction (MiC) is an innovative solution to address housing demands in megacities, offering cost-effectiveness and sustainability. However, stakeholders in MiC projects face challenges in information sharing. Blockchain technology provides unified standards and protocols for decentralized information sharing, aiming to tackle information fragmentation and discontinuity in MiC projects.
COMPUTERS IN INDUSTRY
(2021)
Article
Engineering, Industrial
Xiang T. R. Kong, Miaohui Zhu, Yu Liu, Kaida Qin, George Q. Huang
Summary: This paper introduces an order batching approach based on an automated system to minimize the processing time and system response time of auction orders. The proposed method achieves better efficiency in order processing according to computational experiments.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Computer Science, Artificial Intelligence
Shiquan Ling, Daqiang Guo, Mingxing Li, Yiming Rong, George Q. Huang
Summary: An assembly cell line (ACL) is a type of cell production practice that was derived from the Toyota Production System and has been rapidly adopted in various industries. It allows workers to perform multiple tasks throughout the entire product assembly process by dividing the conveyor line into assembly cells. However, the lack of real-time information sharing makes it difficult to coordinate the capacities of different assembly cells in complex manufacturing environments. To address this issue, this paper proposes a smart ACL system that uses artificial intelligence and IoT technologies to synchronize demand and capacity, improving production efficiency.
JOURNAL OF INTELLIGENT MANUFACTURING
(2022)
Article
Computer Science, Interdisciplinary Applications
S. Y. Wang, George Q. Huang
Summary: In an Industry 4.0 Factory, physical entities are digitized into digital twins with smart IoT devices, resulting in Cyber-Physical Production Systems (CPPS). Real-time data analytics provides traceability and visibility in both the physical and cyber domains. This paper introduces the concept of cyber-physical inventory, or meta-inventory, to Industry 4.0 CPPS. The use of meta-inventory can reduce complexity and uncertainties, and achieve resilience without incurring holding costs.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2023)
Article
Computer Science, Interdisciplinary Applications
Arjun Rachana Harish, X. L. Liu, Ming Li, Ray Y. Zhong, George Q. Huang
Summary: E-commerce logistics financing drives growth in small and medium-sized logistics companies, but faces challenges in information asymmetry, hidden centrality, and information ownership opaqueness. Blockchain technology is considered promising to address these concerns through shared ledger, smart contracts, and tokens. This study introduces a blockchain-enabled cyberphysical traceability system for logistics financing based on digital asset tokenization, bringing visibility and traceability to supply chain transactions. The system's design and implementation are presented, along with its application in logistics financing, which offers resolution and reduced upfront expenditure for stakeholders.
COMPUTERS IN INDUSTRY
(2023)
Proceedings Paper
Computer Science, Information Systems
Mingxing Li, Daqiang Guo, George Q. Huang
Summary: The widespread adoption of Industry 4.0 technologies in factories is transforming manufacturing operations management. Real-time data are acknowledged as beneficial for this management, and utilizing these data to facilitate production and intralogistics operations is an emerging challenge. This study proposes the concept of operation twins for achieving synchronized PiL operations based on three dimensions of synchronization.
ADVANCES IN PRODUCTION MANAGEMENT SYSTEMS: ARTIFICIAL INTELLIGENCE FOR SUSTAINABLE AND RESILIENT PRODUCTION SYSTEMS, PT V
(2021)
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)
