Production and Operations Management Powered by Artificial Intelligence and Data Analytics
A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Management".
Deadline for manuscript submissions: 31 May 2024 | Viewed by 5585
Special Issue Editors
Interests: artificial intelligence; data analytics; project management
Interests: supply chain management; scheduling and optimization
Special Issues, Collections and Topics in MDPI journals
Interests: production scheduling; logistics management
Special Issue Information
Dear Colleagues,
In today’s highly competitive and globalized market environment, in order to maintain a long-term competitive advantage, it is vital for companies to adopt sustainable and effective production and operations management methods. Therefore, both the industry and academia devote resources to developing various approaches based on computer, decision, and mathematical sciences to deal with complex decision problems that arise in production and operations management.
Recent years have witnessed significant advances in artificial intelligence and data analytics. There has been a growing research effort that attempts to develop and apply artificial intelligence and data analytics methods that are suitable for production and operations management problems. Artificial intelligence and data analytics provide promising data-driven opportunities for improving the delivery of products and services by better using limited resources.
This Special Issue seeks to champion the integration of artificial intelligence and data analytics into production and operations management. Original research articles and reviews are welcomed in this Special Issue, encompassing a broad spectrum of research areas with a focus on promoting sustainability. Potential research domains include, but are not confined to, the following:
- Sustainable production and operations management;
- Production and operations management based on artificial intelligence (machine learning, data mining, metaverse, etc.);
- Production and operations management based on data analytics;
- Data-driven production and operations management;
- Production planning and scheduling;
- Project management and scheduling;
- Logistics and supply chain management;
- Information systems and operations management;
- Product innovation and technology management;
- Optimization models and exact/meta-heuristic algorithms in production and operations management.
We look forward to receiving your contributions.
Dr. Hongbo Li
Prof. Dr. Wenchao Wei
Dr. Hongli Zhu
Dr. Fang Xie
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- production and operations management
- artificial intelligence
- data analytics
- sustainability
- optimization