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Special Issue on Operations Research and Machine Learning
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Go to submission site (link opens in a new window)Information Systems and Operational Research (INFOR) publishes original high quality papers in the areas of data analytics and operations research. We focus on the theory, methodology and practice of Data Analytics and Operations Research and are particularly interested in papers that explore elements of both subjects.
We welcome papers that examine the following topics:
We accept the following forms of submission:
Application: As a medium of communication between academics and practitioners, INFOR welcomes papers that demonstrate novel OR and IS approaches and concepts applied to important practical situations.
Theory: Original contributions to the techniques and methodology of data analytics and operations research. Authors should clearly demonstrate the relevance of the results in terms of applications.
Reviews: State-of-the-art surveys that review major theory and application development.
Notes: Short technical communications and comments on previously published INFOR papers.
We operate a rigorous single-anonymized peer review process. Visit our Instructions for Authors page for information on preparing your manuscript.
Author benefits
INFOR is abstracted and indexed in several leading databases including the Science Citation Index, Scopus, CABS Journal Guide and more.
We are published on behalf of the Canadian Operational Research Society meaning your research will be accessible to all their members.
The prestigious and experienced members of our international Editorial Board will guide you from submission to publication
Our Author Services page provides you with tips and tricks to promote your research on social media and through your network. This includes 50 free e-prints to share with anyone you wish.
Quickly and easily track the impact your paper makes with the help of Authored Works.
Authors can choose to publish gold open access in this journal.
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Special Issue on Operations Research and Machine Learning
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