Collection

Operations Research & Machine Learning and Artificial Intelligence

Submission status
Closed
Operational research (OR) and optimization methods play an important role in tackling complicated problems in a wide range of fields. These methods facilitate problem-solving leading to better decision making. Breaking complex problems into multiple simpler sub-problems and solving them is called OR which is a promising problem-solving tool. Machine learning (ML) and artificial intelligence (AI) are both branches of computer science. These are the two most popular technologies for developing intelligent systems. The interplay between OR, ML and Al is one of the most significant achievements in modern computer science. OR and optimization techniques are crucial in the process of developing algorithms in ML and AI. However, ML and AI are not simply consuming OR and optimization techniques; they are rapidly expanding fields that are generating new OR and optimization ideas and helping to solve problems in these disciplines.

This special issue aims to consider cutting-edge approaches for interaction between OR, ML, and AI in a way useful to scholars in all these disciplines.

The special issue covers but is not limited to the following topics:

Operations Research

Optimization

Machine Learning

Artificial Intelligence

OR for ML and AI

ML and AI for OR

Supervised learning

Semi-supervised learning

Unsupervised learning

Deep learning

Big data

Applications of OR, Optimization, ML and AI in domains such as robotics, business, energy and power systems, health care, environmental sciences, portfolio analysis and all other relevant areas.

Submission Instructions: Papers should be submitted at the Operations Research Forum website. Please choose the option " Operations Research & Machine Learning and Artificial Intelligence”. The papers will be reviewed according to the editorial policy & standards of Operations Research Forum. Authors who are interested on the topics related to this special issue can submit their original and novel work. They should be noticed that their work should not be published or be currently under consideration for publication elsewhere. Also, they are not allowed to submit their work to a journal or a conference during the review process. Previously published conference papers are allowed for submission provided that they are extended substantially and cite the published conference paper. A clear indication of the motivation and comparison with prior related work should be presented. Prior to submission, please ensure that your paper adheres to the journal’s author guidelines, which can be found at:

https://www.springer.com/journal/43069/submission-guidelines

Editors

  • Hossein Moosaei Hossein Moosaei , 

    Hossein Moosaei

    Jan Evangelista Purkyně University, Czech Republic hossein.moosaei@ujep.cz

  • Panos M. Pardalos Panos M. Pardalos , 

    Panos M. Pardalos

    University of Florida, USA pardalos@ise.ufl.edu

  • Roohallah Alizadehsani Roohallah Alizadehsani  &

    Roohallah Alizadehsani

    Deakin University, Australia r.alizadehsani@deakin.edu.au

  • Jiří Škvor Jiří Škvor

    Jiří Škvor

    Jan Evangelista Purkyně University, Czech Republic jiri.skvor@ujep.cz

Articles (6 in this collection)