A Population-Based Computational Framework for Analyzing and Mitigating Project Management Delays in Smart Grid Development

This paper highlights the significance of bi-objective optimization in project management and the potential of dynamic programming approaches to simplify complex industrial management situations. The study investigates the relationships between variables inside systems by employing algorithmic comparisons and the analytic hierarchy approach, so offering valuable insights into the efficacy of project management. The statistics reveals a stark reality: a mere 20.5% of projects are finished prior to the designated date. The occurrence of delays in most projects underscores the importance of project managers employing bi-objective optimization methodologies. To deal with the inherent challenges and uncertainties, the study suggests implementing a wide range of these tactics, which will ultimately enhance the success rates of projects.