49 citations · 53 across the 4 of their papers we have counts for
4 papers
An Innovative Data-Driven and Adaptive Reinforcement Learning Approach for Context-Aware Prescriptive Process Monitoring
Mostafa Abbasi, Maziyar Khadivi, Maryam Ahang +3
The application of artificial intelligence and machine learning in business process management has advanced significantly, however, the full potential of these technologies remains…
A mathematical model for simultaneous personnel shift planning and unrelated parallel machine scheduling
Maziyar Khadivi, Mostafa Abbasi, Todd Charter +1
This paper addresses a production scheduling problem derived from an industrial use case, focusing on unrelated parallel machine scheduling with the personnel availability constrai…
Intelligent Condition Monitoring of Industrial Plants: An Overview of Methodologies and Uncertainty Management Strategies
Maryam Ahang, Todd Charter, Mostafa Abbasi +3
Condition monitoring is essential for ensuring the safety, reliability, and efficiency of modern industrial systems. With the increasing complexity of industrial processes, artific…
Deep reinforcement learning for machine scheduling: Methodology, the state-of-the-art, and future directions
Maziyar Khadivi, Todd Charter, Marjan Yaghoubi +4
Machine scheduling aims to optimize job assignments to machines while adhering to manufacturing rules and job specifications. This optimization leads to reduced operational costs,…