Article
Engineering, Industrial
Jun Guo, Zhipeng Pu, Baigang Du, Yibing Li
Summary: The paper introduces a hybrid production line balancing problem that considers the similarity between assembly and disassembly tasks. A mathematical model of the multi-objective stochastic hybrid production line balancing problem is presented, and a hybrid VNS-NSGA II algorithm is proposed to solve it, demonstrating the superiority of the hybrid production line and the effectiveness of the proposed method through computational comparisons and case studies.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Engineering, Industrial
Mohammed-Amine Abdous, Xavier Delorme, Daria Battini, Sandrine Berger-Douce
Summary: Manufacturing systems are social-technical systems that involve interactions between humans and technologies in shared workspaces. Collaborative manufacturing systems combine the benefits of human workers and Industry 4.0 technologies and are useful in flexible and adaptable contexts. The key problems in designing these systems are line balancing and equipment selection. We propose a multi-objective approach that optimizes investment costs and ergonomics, and developed a solving algorithm based on epsilon-constraint to achieve a trade-off between these objectives.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Engineering, Industrial
Zikai Zhang, Qiuhua Tang, Dayong Han, Xinbo Qian
Summary: This paper proposes multiple alternative assignment plans with interchangeable abilities to improve production continuity during preventive maintenance. A mixed-integer mathematical model is formulated to minimize cycle time and total assignment plan alteration cost. An enhanced JAYA algorithm is developed to effectively and efficiently obtain well-distributed Pareto frontier solutions.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Automation & Control Systems
Hongying Shan
Summary: This study examines the practical application of assembly line-Seru conversion in a Chinese electronics assembly company during the C2M transition. It proposes a production line improvement scheme and uses mathematical modeling and algorithms to determine the optimal solution.
ASSEMBLY AUTOMATION
(2022)
Article
Computer Science, Interdisciplinary Applications
Mohd Fadzil Faisae Ab Rashid, Nik Mohd Zuki Nik Mohamed, Ahmad Nasser Mohd Rose
Summary: This research presents an integrated assembly sequence planning and assembly line balancing optimization model for a two-sided assembly environment. By using a multi-objective multi-verse optimizer and considering line efficiency, reorientation penalty, and tool change as optimization objectives, the efficiency of the assembly line can be improved. Additionally, the best decoding method was determined and compared with other multi-objective optimization algorithms, with the proposed algorithm showing better convergence and solution distribution.
JOURNAL OF COMBINATORIAL OPTIMIZATION
(2022)
Article
Computer Science, Artificial Intelligence
Xiaolong Li, Yang Yu, Min Huang
Summary: This study proposes a multi-objective cooperative coevolution algorithm for optimizing Seru Production. The algorithm utilizes a cooperative mechanism to simultaneously optimize seru formation and seru scheduling, and improves the quality of solutions by defining and using non-dominated solutions. To reduce computational time, parallel evolution is implemented, and the quality of solutions is further enhanced by a Master-Slave mechanism.
APPLIED SOFT COMPUTING
(2022)
Article
Computer Science, Interdisciplinary Applications
Parames Chutima, Arthit Khotsaenlee
Summary: This paper presents a mathematical model for the parallel adjacent U-shaped assembly line balancing problem, which involves human workers, robots, and disabled workers. It optimizes five objectives related to the system as a whole and three other entities simultaneously. A reference point based evolutionary algorithm, NSTLBO III, is proposed to solve the NP-hard problem, and its performance is compared with two other well-known multi-objective evolutionary algorithms.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Computer Science, Theory & Methods
Shouyong Jiang, Juan Zou, Shengxiang Yang, Xin Yao
Summary: Evolutionary dynamic multi-objective optimisation (EDMO) is a rapidly growing area that uses evolutionary approaches to solve multi-objective optimisation problems with time-varying changes. After nearly two decades, significant advancements have been made in theoretic research and applications. This article provides a comprehensive survey and taxonomy of existing research on EDMO, as well as highlighting multiple research opportunities for further development.
ACM COMPUTING SURVEYS
(2023)
Article
Engineering, Industrial
Thiago Cantos Lopes, Adalberto Sato Michels, Nadia Brauner, Leandro Magatao
Summary: This paper focuses on optimizing Mixed-model assembly lines with continuous paced line control and proposes a criterion-space method for defining the Pareto front. Comparing the Pareto fronts between cycle time and line length for paced and unpaced lines allows meaningful comparisons between line controls. An industrial case study suggests that paced lines are more efficient than unpaced lines for lower cycle time ranges.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Lue Tao, Yun Dong, Weihua Chen, Yang Yang, Lijie Su, Qingxin Guo, Gongshu Wang
Summary: This study addresses a new variant of the assembly line feeding problem in automobile manufacturing, proposing a novel mathematical model and algorithm that achieve superior cost savings, solution quality, and convergence efficiency while providing decision support for managers.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Zixiang Li, Mukund Nilakantan Janardhanan, S. G. Ponnambalam
Summary: This study investigates the cost-oriented robotic assembly line balancing problem, including purchasing cost and setup time optimization, by developing a mixed-integer linear programming model. The proposed IMABC algorithm introduces new employed bee phase and scout phase to enhance exploration and exploitation.
JOURNAL OF INTELLIGENT MANUFACTURING
(2021)
Article
Engineering, Industrial
Weibo Ren, Jingqian Wen, Yan Yan, Yaoguang Hu, Yu Guan, Jinliang Li
Summary: This paper proposes a methodology for multi-objective optimisation of energy-aware flexible job-shop scheduling by developing a mixed integrated mathematical model and heuristic algorithm. Numerical examples demonstrate the effectiveness and performance of the method in achieving energy awareness in manufacturing systems.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2021)
Article
Engineering, Industrial
Xiaofeng Xu, Ziru Lin, Xiang Li, Changjing Shang, Qiang Shen
Summary: This study addresses the refined oil distribution problem with shortages using a multi-objective optimization approach, including a robust optimization model (ROM) to manage uncertainty in demand and a multi-objective particle swarm optimization (MOPSO) algorithm. Results show that these models and algorithms effectively improve station satisfaction, reduce operation costs and overtime penalties, providing possibilities for the efficient distribution of scarce resources.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Engineering, Industrial
Rifat Ozdemir, Ilkan Sarigol, Sarah AlMutairi, Sarah AlMeea, Abrar Murad, Aseel Naqi, Noor AlNasser
Summary: The main focus of this study is to develop a model to design assembly lines with ergonomic risk consideration, addressing factors such as assembly line balancing, component weight, and worker posture through ergonomic risk analysis and a fuzzy multi-objective model.
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS
(2021)
Article
Green & Sustainable Science & Technology
Ridoy Das, Yue Wang, Krishna Busawon, Ghanim Putrus, Myriam Neaimeh
Summary: This study proposes a real-time multi-objective optimization method to balance different objectives by scheduling the charging/discharging profile of electric vehicles, including reducing electricity costs, minimizing battery degradation, alleviating grid stress, and meeting the charging requirements of EV users.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Management
Yu Zhang, Yu Wang, Jiafu Tang, Andrew Lim
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2020)
Article
Statistics & Probability
Xuanzhu Fan, Jiafu Tang, Chongjun Yan
COMPUTATIONAL STATISTICS
(2020)
Article
Engineering, Multidisciplinary
Chengkuan Zeng, Jiafu Tang, Zhi-Ping Fan, Chongjun Yan
ENGINEERING OPTIMIZATION
(2020)
Article
Engineering, Industrial
Wei Qi, Xinggang Luo, Yang Yu, Jiafu Tang
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2020)
Article
Management
Dehai Liu, Xiaoxian Ji, Jiafu Tang, Hongyi Li
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2020)
Article
Computer Science, Interdisciplinary Applications
Xuanzhu Fan, Jiafu Tang, Chongjun Yan, Hainan Guo, Zhongfa Cao
Summary: In medical outpatient services, inefficiency of resource utilization and patient dissatisfaction are major issues. A simulation optimization framework was proposed to optimize scheduling, considering patient preferences and patience limits, with a data-driven discrete event simulation model. Validated through real data, the optimization method comprehensively improves the performance of the outpatient service scheduling system.
JOURNAL OF COMBINATORIAL OPTIMIZATION
(2021)
Article
Operations Research & Management Science
Ye Wang, Jiafu Tang
Summary: This research focuses on optimizing the configuration for implementing the seru production system (SPS) under uncertain demand, aiming to formulate a robust production system capable of effectively responding to stochastic demands. The study addresses the issues of determining the required amount of skill training and matching workers with their corresponding skills. A stochastic optimization model and heuristic algorithm are developed to minimize the total expected cost of the system, taking into account various cost factors. Experimental results show the benefits of appropriate partial skill training and the relationship between total cost, skill training, demand fluctuations, and product types.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Operations Research & Management Science
Chang Liu, Zhen Li, Jiafu Tang, Xuequn Wang, Ming-Jong Yao
Summary: In the context of Chinese firms, the SERU production system shows greater manufacturing flexibility, with multi-skilled worker involvement being a key factor in improving flexibility and impacting firm performance.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Engineering, Multidisciplinary
Chengkuan Zeng, Zixuan Liu, Jiafu Tang, Zhi-Ping Fan, Chongjun Yan, Siyuan Long
Summary: This study proposes a solution to cooperative batch scheduling problems using both serial batch and parallel batch scheduling methods. A mixed-integer linear programming model is used to describe the problem and a bid construction scheme is developed for solving it. Experimental results show that the proposed scheme can quickly and effectively identify feasible solutions, making it suitable for addressing cooperative batch scheduling problems, especially those corresponding to large-scale instances.
ENGINEERING OPTIMIZATION
(2023)
Article
Business, Finance
Yin Gai, Yong Yin, Jiafu Tang, Shiqiang Liu
Summary: This paper discusses the minimization of makespan in a seru production system through the use of an optimal seru loading policy. The problem is formulated as a min-max integer optimization model and an exact dimension-reduction algorithm is developed to obtain the optimal allocation. Experimental comparisons with a greedy algorithm demonstrate the usefulness and efficiency of the developed algorithm.
JOURNAL OF MANAGEMENT SCIENCE AND ENGINEERING
(2022)
Article
Business, Finance
Chongjun Yan, George G. Q. Huang, Yong-Hong Kuo, Jiafu Tang
Summary: This study addresses the issue of uncertainty in appointment systems by considering patient needs and preferences, and proposes a myopic scheduling policy based on a stochastic overbooking model. The objective is to maximize the expected profit and improve the performance of outpatient clinics.
JOURNAL OF MANAGEMENT SCIENCE AND ENGINEERING
(2022)
Article
Green & Sustainable Science & Technology
Muyang Wen, Wei Sun, Yang Yu, Jiafu Tang, Kaku Ikou
Summary: This paper proposes an improved adaptive large neighborhood search (ALNS) algorithm to efficiently solve the multi-depot green vehicle routing problem. The algorithm utilizes problem-specific destroy and repair operators to optimize the route planning process and improve computational efficiency and accuracy.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Engineering, Manufacturing
Yu Wang, Yu Zhang, Minglong Zhou, Jiafu Tang
Summary: This paper enhances the accuracy of surgery duration models by segmenting patient features, classifying patients into different types using machine learning, and minimizing overtime risks. The model is easily interpretable to healthcare practitioners as it is equivalent to minimizing a Fano factor.
PRODUCTION AND OPERATIONS MANAGEMENT
(2023)
Article
Engineering, Industrial
Yuhong Ren, Jiafu Tang, Yang Yu, Xiaolong Li
Summary: This paper discusses the formation of flexible seru systems, particularly focusing on the strategic decision phase. The Flexible Seru System Formation Problem (FSFP) is formulated as a nonlinear programming model to evaluate flexibility performance. By transforming the model into a linear one and using Gurobi solver, the optimal solution is obtained. For large-scale problems, a parallel Master-Slave adaptive genetic algorithm (PMSA-GA) is proposed. The experiments demonstrate that the FSFP model is more suitable for dynamic demand environments than the task-oriented seru formation (TOSF) strategy from previous literature.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2023)
Article
Computer Science, Interdisciplinary Applications
Yiming Liu, Yang Yu, Yu Zhang, Roberto Baldacci, Jiafu Tang, Xinggang Luo, Wei Sun
Summary: Motivated by environmental concerns, this study addresses the time-dependent green vehicle routing problem with time windows (TDGVRPTW) aiming to minimize carbon emissions. An exact method based on a branch-cut-and-price algorithm is proposed and tested on benchmark instances. The results demonstrate the effectiveness of the method in solving TDGVRPTW instances involving up to 100 customers. The study is valuable for researchers and provides practical insights for practitioners.
INFORMS JOURNAL ON COMPUTING
(2022)
