Application of Computational Intelligence and Machine Learning to Conventional Operational Research Methods
Application of Computational Intelligence and Machine Learning to Conventional Operational Research Methods
Date
2022
item.page.datecreated
Authors
Ali, Atif
Said, Raed A.
Rizwan, Hafiz Muhammad Amir
Shehzad, Khurram
Naz, Imran
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers Inc.
Abstract
Machine learning and computational intelligence are two methods for achieving this (CI); traditional operational research methods are combined with machine learning-based computational techniques (OR). Students can handle complex decision-making problems thanks to the synergy between those methods and techniques. This research's primary goal is to present and demonstrate potential connections amid the two computational arenas. Using applications, we show how machine learning techniques like fuzzy logic, neural networks and reinforcement learning can be combined to provide a simpler solution to more complex problems than traditional OR methods., which is a research contribution in and of itself. © 2022 IEEE.
Description
This conference paper is not available at CUD collection. The version of scholarly record of this paper is published in 2022 International Conference on Business Analytics for Technology and Security (ICBATS) (2022), available online at: https://doi.org/10.1109/ICBATS54253.2022.9759033
item.page.type
Conference Paper
item.page.format
Keywords
Hybrid Models , Machine Learning , Operational Research , Optimization
Citation
Ali, A., Said, R. A., Rizwan, H. M. A., Shehzad, K., & Naz, I. (2022). Application of computational intelligence and machine learning to conventional operational research methods. 2022 International Conference on Business Analytics for Technology and Security (ICBATS). https://doi.org/10.1109/ICBATS54253.2022.9759033