EURO Bulletin Board - Publications
Cal for Papers. Metaheuristics for Sustainable Manufacturing. Submission Deadline: October 31, 2024.
https://www.sciencedirect.com/journal/engineering-applications-of-artificial-intelligence/about/call-for-papers
The term manufacturing refers to the secondary industry in the supply chain domain in which a type of raw material is converted into a product usable to the customer. Generally, manufacturing involves the utilization of labor, traditional and automated machine tools, chemical, and biological processes, assembly, etc. The customer could be the end-user or next level of the supply chain in which the product could be transformed with added value or assembled further with other products. For the manufacturing industry to survive and thrive innovation, quality, safety, and competitiveness must be achieved at the minimum cost, i.e., efficiently utilizing the available resources such as material, labor, machines tools, land, time, robots, computer software and hardware, etc. As manufacturing is generally carried out on a large scale, any efficiency improvement in the utilization of these resources impacts positively on the entire supply chain and the end product. The result could be reduction in the overall cost of manufacturing, reduction in pollution and waste, improvement in the quality of the product, increase in customer satisfaction, etc., which eventually nurtures sustainability. It is important in global viewpoint especially for developing countries where the production is being outsourced and the customer market is all over the world.
The efficient utilization here refers to the minimization of cost, and maximization of yield satisfying the constraints. There are several classical optimization approaches have been studied in the literature and being applied in the manufacturing industries for optimizing several associated parameters and variables. The common optimization approaches are associated with Linear Programming Problem and heuristics. However, as the manufacturing designs are becoming more complex and miniature with inclination towards increase in variety, quality improvement and cost minimization, it is becoming essential to develop and employ novel optimization techniques which can handle a variety of class of data, give the rich and acceptable quality of solutions at reasonable computational cost. In recent times, several Artificial Intelligence (AI) based nature-inspired optimization methods have been proposed. They are commonly referred to as metaheuristics. They could be further classified as bio-inspired, socio-inspired and physics-based methods. The methods are driven by simple rules in the specific algorithmic framework. So far, these algorithms have been applied in several domains such as transportation, healthcare, design engineering, etc.; however, optimization-related discussion in the multifaceted domain of manufacturing is still quite limited. The issue can accommodate the original contributions from within the below domains (not limited to):
1. Novel or modified metaheuristics for manufacturing quality control and reliability
2. Metaheuristic solutions to enhance process efficiency and sustainability
3. Nature-inspired optimization methods in production, manufacturing and logistics
4. Metaheuristic solutions to human resource and safety
5. Metaheuristic solutions to Industrial waste Management
6. Metaheuristic solutions to material movement and handling systems
7. Novel or modified metaheuristics for machining processes
8. Novel or modified metaheuristics for manufacturing processes
9. Metaheuristic solutions to improve energy consumption
Guest editors:
Dr. Anand J Kulkarni (Executive Guest Editor)
MIT World Peace University, Pune, India
Email: [email protected]
Areas of Expertise: optimization, metaheuristics
Dr. Patrick Siarry
Université Paris-Est Creteil, Creteil, France
Email: [email protected]
Areas of Expertise: optimization, metaheuristics
Manuscript submission information:
Tentative Schedule:
- Submission Open Date: April 30, 2024
- Submission Deadline: October 31, 2024
- Notification of Acceptance: February 28, 2025
Contributed papers must be submitted via the Engineering Applications of Artificial Intelligence online submission system (Editorial Manager®): Please select the article type “VSI: Meta for Sust Mfg” when submitting the manuscript online.
Please refer to the Guide for Authors to prepare your manuscript.
For any further information, the authors may contact the Guest Editors.
Keywords:
(optimization) AND (metaheuristics) AND (artificial intelligence) AND (manufacturing) AND (sustainability)
Posted on 2024-06-27 by Sarah Fores