Article
Engineering, Industrial
Harun Aydilek, Asiye Aydilek, Muberra Allahverdi, Ali Allahverdi
Summary: This paper addresses the no-wait constraint in a manufacturing environment and proposes two new dominance relations and constructive heuristics that are more efficient than existing methods in the literature.
INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING COMPUTATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Qing-qing Zeng, Jun-qing Li, Rong-hao Li, Ti-hao Huang, Yu-yan Han, Hong-yan Sang
Summary: This paper addresses a multi-objective energy-efficient scheduling problem of the distributed permutation flowshop with sequence-dependent setup time and no-wait constraints. It proposes a new mixed-integer linear programming model and an improved non-dominated sorting genetic algorithm, along with problem-specific heuristics and search operators, to enhance the algorithm performance.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Chen-Yang Cheng, Pourya Pourhejazy, Kuo-Ching Ying, Yi-Hsiu Liao
Summary: This study successfully addressed the No-wait Flowshop Group Scheduling Problems, achieving a best-found solution rate of over 99.7% through the development of two metaheuristics. The results indicate that RMSA outperforms existing algorithms for solving the NWFGSP_SDST problem.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Interdisciplinary Applications
Karam Allali, Said Aqil, Jabrane Belabid
Summary: This paper investigates a multi-objective optimization distributed no-wait permutation flow shop scheduling problem under the constraint of sequence dependent setup time. The study proposes mixed integer linear programming and several efficient metaheuristics to solve this industrial problem. The combination of the genetic algorithm and Nawaz-Enscore-Ham algorithm yields the best results.
SIMULATION MODELLING PRACTICE AND THEORY
(2022)
Article
Computer Science, Information Systems
Jianming Dong, Hong Pan, Cunkui Ye, Weitian Tong, Jueliang Hu
Summary: Efficient resource arrangement is crucial for creating intelligent management systems in hospitals. This study introduces the no-wait two-stage flowshop scheduling problem with multi-task flexibility on the first-stage machine, aiming to minimize the maximum completion time of all jobs. Several novel structural properties are discovered, leading to a linear-time combinatorial algorithm with an approximation ratio of 13/8.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Artificial Intelligence
Li Haoran, Li Xinyu, Gao Liang
Summary: With the development of globalization, distributed manufacturing has become a main mode of manufacturing. This paper addresses a distributed heterogeneous no-wait flowshop scheduling problem (DHNWFSP) and proposes a discrete artificial bee colony algorithm (DABC) to effectively solve it, considering the heterogeneity between factories in distributed flow-shop scheduling for the first time. The proposed DABC achieves the highest-quality solutions in comparison with state-of-art algorithms, as shown by numerical experiments for small and large-scale problems.
APPLIED SOFT COMPUTING
(2021)
Article
Engineering, Multidisciplinary
Muberra Allahverdi, Harun Aydilek, Asiye Aydilek, Ali Allahverdi
Summary: This paper examines a manufacturing system with a two-machine no-wait flowshop scheduling problem and introduces a new dominance relation. Constructive heuristics are proposed to solve real-life problems, with computational experiments showing good performance.
JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION
(2021)
Article
Metallurgy & Metallurgical Engineering
Hua Xuan, Qianqian Zheng, Bing Li, Xueyuan Wang
Summary: The paper presents a study on scheduling N jobs in a hybrid flowshop with unrelated parallel machines, proposing a novel genetic simulated annealing algorithm to address the problem effectively. The algorithm includes an adaptive adjustment strategy to avoid premature convergence and enhance search ability, along with a simulated annealing procedure for re-optimization of better individuals from the genetic algorithm solutions. Computational results show that the algorithm outperforms several heuristic algorithms reported in the literature.
ISIJ INTERNATIONAL
(2021)
Article
Automation & Control Systems
Fuqing Zhao, Tao Jiang, Ling Wang
Summary: Green manufacturing has gained increasing attention in the context of carbon peaking and carbon neutrality. Distributed production is prevalent in various manufacturing industries due to globalization. This article addresses the energy-efficient distributed no-wait flow-shop scheduling problem with sequence-dependent setup time (DNWFSP-SDST) for minimizing makespan and total energy consumption (TEC). A mixed-integer linear programming model is formulated, and a cooperative meta-heuristic algorithm based on Q-learning (CMAQ) is proposed. The experimental results demonstrate that CMAQ outperforms state-of-the-art comparison algorithms in solving energy-efficient DNWFSP-SDST.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Multidisciplinary
Bruno de Athayde Prata, Marcelo Seido Nagano
Summary: This study proposes an innovative iterated greedy algorithm for the no-wait permutation flowshop layout problem. The algorithm outperforms five other algorithms in terms of two performance measures.
ENGINEERING OPTIMIZATION
(2022)
Article
Engineering, Multidisciplinary
Marcelo Seido Nagano, Fernando Siqueira de Almeida, Hugo Hissashi Miyata
Summary: This article proposes an iterated greedy-with-local-search algorithm for the no-wait flowshop scheduling problem, which outperforms both the mathematical model and the best existing algorithm in terms of effectiveness and efficiency according to computational experiments and statistical analysis.
ENGINEERING OPTIMIZATION
(2021)
Article
Automation & Control Systems
Mustafa Avci
Summary: The distributed no-wait flowshop scheduling problem (DNWFSP) is a variant of the classical flowshop scheduling problem. An iterated local search (ILS) algorithm is proposed to solve the DNWFSP, which incorporates specialized local search and adaptively adjusted perturbation strength. The ILS is able to produce high-quality solutions in short computing times.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Interdisciplinary Applications
Danyu Bai, Xiaoyuan Bai, Jie Yang, Xingong Zhang, Tao Ren, Chenxi Xie, Bingqian Liu
Summary: In fiercely competitive industries, customer satisfaction is crucial for modern enterprises, and reducing delivery lateness is an effective strategy to achieve this. This study focuses on optimizing maximum lateness in flowshop scheduling, introducing learning effects and individual release dates for tasks. Exact and approximate algorithms are proposed to handle different production scenarios, and heuristic methods and metaheuristic algorithms are employed to obtain high-quality solutions efficiently. Performance enhancements are achieved through various techniques, including asymptotic analysis, branch and bound algorithm, and discrete artificial bee colony algorithm with hybrid neighborhood search. Numerical simulations demonstrate the advantages of the proposed algorithms in addressing the scheduling optimization problem.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Mathematics
Muberra Allahverdi
Summary: This article investigates the problem of minimizing total completion time in an uncertain environment. By establishing a more effective mathematical dominance relation, it is found that the average improvement compared to the existing literature is 1407.80%. Furthermore, statistical hypothesis testing and confidence intervals confirm the accuracy of the established dominance relation.
HACETTEPE JOURNAL OF MATHEMATICS AND STATISTICS
(2023)
Article
Computer Science, Artificial Intelligence
Yan Qiao, NaiQi Wu, YunFang He, ZhiWu Li, Tao Chen
Summary: This paper investigates the scheduling problem of a class of two-stage hybrid flow shops and proposes an adaptive genetic algorithm and a local search method to solve it. The experiments show that the proposed method can find high-quality solutions in a short time.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Engineering, Industrial
King-Wah Pang, Hau-Ling Chan
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2017)
Article
Economics
Wen Jiao, Hong Yan, King-Wah Pang
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL
(2016)
Article
Computer Science, Artificial Intelligence
King-Wah Pang
EXPERT SYSTEMS WITH APPLICATIONS
(2011)
Article
Engineering, Industrial
King-Wah Pang, Jiyin Liu
Article
Engineering, Industrial
King-Wah Pang, Zhou Xu, Chung-Lun Li
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2011)
Article
Engineering, Industrial
Ping Zhang, King-Wah Pang, Hong Yan
Summary: This study aims to explore a coordinating mechanism for sharing and return actions of retailers in the medical supply chain. By comparing the viewpoints of dealers and retailers, the differences between dealer-dominated sharing and retailer-dominated sharing are analyzed in terms of sharing performance and expected profits. The study also examines the conditions under which dealers benefit from retailers' sharing when they have the power to encourage sharing, as well as the dealer's preference for non-cooperative retailers or cooperative retailers when they lack the power to encourage sharing.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Education & Educational Research
Kin Cheung, Jeremy Ng, Hilda Tsang, King Wah Pang
Summary: This study in an Asian context investigated factors predicting academic performance and degree attainment of vertical transfer students in Hong Kong. It found that factors such as gender, GPA, and number of courses were significant predictors of baccalaureate degree attainment, while transfer shock and required credits per year were negative predictors.
STUDIES IN EDUCATIONAL EVALUATION
(2021)
Article
Computer Science, Software Engineering
K Tang, A Pang
COMPUTER-AIDED DESIGN
(2003)
Article
Engineering, Industrial
A Pang, A Joneja, DCC Lam, M Yuen
Article
Management
Chung-Lun Li, King-Wah Pang
INTERNATIONAL JOURNAL OF SHIPPING AND TRANSPORT LOGISTICS
(2011)
Article
Management
Y. H. Venus Lun, K. W. Pang, Photis M. Panayides
INTERNATIONAL JOURNAL OF SHIPPING AND TRANSPORT LOGISTICS
(2010)
Article
Engineering, Industrial
APK Wah, A Joneja
JOURNAL OF MANUFACTURING SYSTEMS
(2003)
Article
Computer Science, Interdisciplinary Applications
A Joneja, A Pang, D Lam, M Yuen
INTERNATIONAL JOURNAL OF COMPUTER INTEGRATED MANUFACTURING
(2000)
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)
