Fine-Tuning Large-Scale Project Scheduling

This paper explores the integration of artificial intelligence (AI) into project management, proposing a decision support system that optimizes project timelines and resources. The pilot study focuses on the Port of Agios Konstantinos in Greece. The methodology section introduces dual annealing as a stochastic optimization method and explains the use of a customizable cost function with overlap calculation to prioritize project aspects. An objective function is defined to maximize task alignment with optimal scheduling periods. The experimental results section presents three optimization cases, adjusting schedules for critical tasks in the pilot project based on different weightings of budget and weather considerations.