https://www.sciencedirect.com/journal/euro-journal-on-computational-optimization/about/call-for-papers
For this SI on the occasion of EURO 2024 in Copenhagen, EJCO invites submission of high-quality and innovative papers focusing on the intersection and interplay of optimization and machine learning.
Guest editors:
Dr. Bissan Ghaddar
[email protected]
Dr. Markus Leitner
[email protected]
Special issue information:
Submitted papers should use or incorporate methods from machine learning to solve challenging optimization problems. Both methodological contributions and innovative applications, typically validated through convincing computational experiments are equally welcome.
Scope and Topics:
Topics of interest include, but are not limited to:
Manuscript submission information:
The Journal’s submission system is open for submissions to our Special Issue. When submitting your manuscript please select the article type “VSI:Machine learning for optimization” so that the article will be considered for the special issue. Please submit your manuscript by 15th December 2024.
The submission link is: https://www.editorialmanager.com/ejcomp
All submissions deemed suitable to be sent for peer review will be reviewed by at least two independent reviewers. Once your manuscript is accepted, it will go into production, and will be simultaneously published in the current regular issue and pulled into the online Special Issue. Articles from this Special Issue will appear in different regular issues of the journal, though they will be clearly marked and branded as Special Issue articles.
Please see an example here: https://www.sciencedirect.com/journal/euro-journal-on-computational-optimization
Please ensure you read the Guide for Authors before writing your manuscript. The Guide for Authors and link to submit your manuscript is available on the Journal’s homepage at Guide for authors - EURO Journal on Computational Optimization - ISSN 2192-4406 | ScienceDirect.com by Elsevier
Inquiries, including questions about appropriate topics, may be sent electronically to the Guest Editors.
Keywords:
Machine learning, mathematical programming, algorithmic enhancements, algorithm selection and design
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