Article
Computer Science, Artificial Intelligence
Lili Wang, Zhe Zhang, Yong Yin
Summary: This paper focuses on the order acceptance and scheduling problem in the divisional seru production system, which can achieve responsiveness, flexibility, and efficiency. A nonlinear integer programming model is established, and a bi-level nested heuristic algorithm is designed. Computational experiments show that the proposed algorithm outperforms the bi-level genetic algorithm in terms of objective value and running time, achieving better results and higher efficiency for divisional seru order acceptance and scheduling problems.
APPLIED SOFT COMPUTING
(2023)
Article
Computer Science, Cybernetics
Shaoyu Zeng, Yinghui Wu, Yang Yu
Summary: This paper investigates the multi-skilled worker assignment problem in Seru production system and proposes a bi-objective mixed-integer nonlinear programming model to minimize the total labor hours and workload unfairness. Three solution approaches are designed and experiments are performed to evaluate their performance. The merged Pareto-fronts obtained from these approaches provide useful information for decision-makers.
Article
Computer Science, Interdisciplinary Applications
Feng Liu, Ben Niu, Muze Xing, Lang Wu, Yuanyue Feng
Summary: This research focuses on the problem of assigning cross-trained workers in seru implementation, proposing a bi-objective mathematical model to minimize completion time and balance worker workload. Exact solutions and a memetic algorithm based on NSGA-II were used, with the K-means-based NSGA-II algorithm showing superior performance in terms of speed and quality.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Chenyang Gao, Jianfeng Ma, Teng Li, Yulong Shen
Summary: This paper proposes an adaptive hybrid particle swarm optimization and differential evolution algorithm to optimize control inputs during formation reconfiguration of UAVs, aiming to minimize flight distance and computing costs. By using a receding horizon control strategy, the shortest movement distance of the UAV group is obtained, reducing computation time.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Management
S. Ehsan Hashemi-Petroodi, Simon Thevenin, Sergey Kovalev, Alexandre Dolgui
Summary: This study investigates the impact of model-dependent task assignment, workforce reconfiguration, and equipment duplication on mixed-model assembly lines. The results show that model-dependent task assignment can significantly reduce equipment costs and the number of workers.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2022)
Article
Robotics
Hyungjoon Yang, Je-Hun Lee, Sang Hyun Lee, Seung Gi Lee, Hyung Rok Kim, Hyun-Jung Kim
Summary: The task assignment and worker balancing problem in assembly lines is crucial for maximizing productivity. This study focuses on a real automotive parts assembly line where multiple workers perform various tasks simultaneously in a workstation, with each worker's processing time varying. New positional constraints are introduced to ensure each worker's working space. The goal is to minimize cycle time, and a filtered beam search algorithm is proposed to efficiently solve large-scale instances.
IEEE ROBOTICS AND AUTOMATION LETTERS
(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
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
Lan Luo, Zhe Zhang, Yong Yin
Summary: Seru production is a manufacturing mode that can achieve efficiency, flexibility, and responsiveness simultaneously. The Just-in-Time Organization System (JIT-OS) is used to manage and control seru production systems by addressing seru formation and sera loading. A simulated annealing and genetic algorithm (SA-GA) has been developed to optimize worker assignment and product allocation in seru production, showing good scalability in practice.
JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION
(2021)
Article
Computer Science, Hardware & Architecture
Jie Lian, Wenjuan Li, Guoli Pu, Pengwei Zhang
Summary: Due to frequent changes in product types, SERUS systems can be rapidly constructed, modified, and dismantled. In order to address the task dispatching, product sequencing, and system reconfiguration problems, a bi-objective mathematical model is proposed and solved using a non-dominated sorting genetic algorithm-II.
SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS
(2023)
Article
Engineering, Industrial
Jie Lian, ChenGuang Liu, Wenjuan Li, Juning Su, Hongquan Xue
Summary: In this paper, we address the task dispatching, product sequencing, and seru reconfiguration problems in seru (cellular production system). We propose a nonlinear mathematical model with the objective of minimizing the total earliness and tardiness. The model is validated through computational examples and the impact of parameters on system performance is analyzed.
EUROPEAN JOURNAL OF INDUSTRIAL ENGINEERING
(2022)
Article
Computer Science, Interdisciplinary Applications
Jakob Snauwaert, Rob Van Eynde, Mario Vanhoucke
Summary: Workers with multiple skills enhance team flexibility and working range, making efficient multi-skilled team formation vital for organizational success. This paper examines different multi-skilled workforce formation problems, focusing on skill availability and workforce size minimization. The study also explores the impact of specific skill and worker characteristics on problem complexity. The authors propose fixed individual and total multi-skilled workforce problems, and conclude by applying the findings to real-life projects and conducting computational experiments on problem hardness.
COMPUTERS & OPERATIONS RESEARCH
(2023)
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
Beren Gursoy Yilmaz, Omer Faruk Yilmaz, Emre Cevikcan
Summary: This study investigates the impact of lot streaming and worker assignment strategies on the workforce scheduling problem in the seru production system. A novel optimization model is developed to minimize average flow time, and the results show that using variable sublots can significantly reduce flow time and improve system performance in operational scenarios.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Computer Science, Interdisciplinary Applications
Rongfan Liu, Ming Liu, Feng Chu, Feifeng Zheng, Chengbin Chu
Summary: This study focuses on the multi-skilled worker assignment and assembly line balancing problem with the consideration of energy consumption. By utilizing a bi-objective optimization approach, a processing time and energy consumption sorted-first rule is developed, which outperforms other algorithms in terms of computational time and solution quality.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)