Mathematics Optimization Algorithms and Scheduling Optimization of Manufacturing Systems

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "D2: Operations Research and Fuzzy Decision Making".

Deadline for manuscript submissions: 30 September 2025 | Viewed by 289

Special Issue Editors


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Guest Editor
College of Mechanical Engineering, Zhejiang University of Technology, Hangzhou 310014, China
Interests: scheduling; optimization; queueing system; manufacturing system

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Guest Editor
Department of Industrial Engineering, Tsinghua University, Beijing 100084, China
Interests: supply chain management; production and operations management; production planning and scheduling; robust optimization

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Guest Editor
College of Economics and Management, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
Interests: scheduling; operations management; smart manufacturing; optimization algorithms
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Guest Editor
State Key Laboratory for Manufacturing Systems Engineering, Faculty of Electronics and Information, School of Automation Science and Engineering, Xi'an 710049, China
Interests: smart manufacturing; intelligent logistics; autonomous mobile robots

Special Issue Information

Dear Colleagues,

Sustainable production and services can be defined as the production and use of products and services in a manner that is socially beneficial, economically viable and environmentally benign over the whole life cycle. In today’s rapidly changing market environment, it is increasingly necessary for industry leaders to implement a sustainable production and service strategy. There is, therefore, a growing commitment within the global research community to explore novel methods that reduce waste and optimize production processes to advance the development of sustainable business practices.

This Special Issue aims to provide a platform for the discussion and communication of high-quality interdisciplinary studies on research and practice in this emerging field. It will address the interactions between technology, consumption and policy to help identify more sustainable solutions for both production and service systems. This Special Issue focuses on the modelling, analysis, optimization, and control of manufacturing and service systems with sustainable concerns. The advancement of new information technologies, such as the Internet of Things, big data, cloud and edge computing, 5G-enabled manufacturing, digital twins, manufacturing services, and artificial intelligence, will enable more powerful model-based and data-driven methods. We particularly welcome the submission of qualitative and quantitative results from researchers and practitioners. 

The scope of this Special Issue includes, but is not limited to, the following topics:

  1. Energy efficient and environment friendly manufacturing and service systems;
  2. Collaborative robots in sustainable manufacturing systems;
  3. Smart logistics management in sustainable manufacturing and service systems;
  4. Human-machine interaction for sustainable production optimization;
  5. Meta-verse in sustainable manufacturing and services;
  6. Resilience in manufacturing;
  7. Real-time control of sustainable production and service processes;
  8. Data-driven modelling, monitoring and control of sustainable production and service processes;
  9. Service-oriented smart manufacturing and robot as a service (RaaS);
  10. AI-based design and optimization in sustainable production and service system;
  11. Digital twin technology and service-oriented manufacturing technology;
  12. Green production and service operations management;
  13. Sustainable industry and services;
  14. Sustainable supply chain management;
  15. Predictive maintenance for sustainable operations;
  16. Eco-design in product development;
  17. Smart factories and the IoT;
  18. Data-driven decision-making in production and operations;
  19. Robotics and automation for eco-friendly operations;
  20. Advanced process control for sustainable operations.

Prof. Dr. Zhi Pei
Dr. Zhihai Zhang
Dr. Jian Chen
Dr. Chaobo Yan
Guest Editors

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Keywords

  • manufacturing system
  • scheduling
  • service-oriented manufacturing
  • intelligent manufacturing
  • sustainable manufacturing
  • optimization methods

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Published Papers (1 paper)

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Research

26 pages, 2688 KiB  
Article
Modeling and Optimization of Cable Production Scheduling by Incorporating an Ant Colony Algorithm
by Changbiao Zhu, Chongxin Wang, Zhonghua Ni, Xiaojun Liu and Abbas Raza
Mathematics 2025, 13(8), 1235; https://doi.org/10.3390/math13081235 - 9 Apr 2025
Viewed by 144
Abstract
With the development of small batch and multi-batch service production mode, manual scheduling by hand has been difficult to adapt to the production of a large number of complex orders. This work proposed a cable production scheduling optimization method based on an ant [...] Read more.
With the development of small batch and multi-batch service production mode, manual scheduling by hand has been difficult to adapt to the production of a large number of complex orders. This work proposed a cable production scheduling optimization method based on an ant colony algorithm, aiming at solving the problems of the inefficiency and underutilization of resources in the process of traditional cable scheduling. Applying an ant colony (ACO) algorithm to solve the production scheduling problem achieved the intelligent scheduling and optimization of production tasks. The method utilizes the search and optimization capabilities of the ant colony algorithm, with the characteristics of the cable production line, achieving a reasonable allocation and scheduling of production tasks. After applying the proposed model to the cable production line, the scheduling scheme generated by the ACO algorithm-based objective order scheduling method reduced the total production time required from 3 days to 2.6882 days, resulting in a 10.04% increase in production efficiency. The results show that the method can effectively improve the production efficiency and resource utilization of the cable production line, and has high practicality and feasibility. Full article
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