2708. Online Delay Detection and Resource Allocation in Projects Using Reinforcement Learning
Invited abstract in session MD-7: Extensions of the Resource-Constrained Project Scheduling Problem, stream Scheduling and Project Management.
Monday, 14:30-16:00Room: Clarendon GR.01
Authors (first author is the speaker)
| 1. | Inkyung Sung
|
| Materials and Production, Aalborg University |
Abstract
This study proposes a Reinforcement Learning (RL)-based model for project delay management by dynamically detecting deviations from expected progress, estimated through a learning curve model. The model identifies potential delays in real time and allocates additional resources to critical tasks when necessary to accelerate project completion. With RL’s adaptive decision-making capabilities, the proposed approach ensures timely project delivery while effectively managing resource availability and the time-cost trade-off.
Keywords
- Artificial Intelligence
- Machine Learning
- Risk Analysis and Management
Status: accepted
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