The College of Computer Science and Information Technology at University of Basrah organized a scientific lecture entitled:

“A Federated Population Initialization Framework for Metaheuristic Algorithms.”

The lecture aimed to highlight the importance of the initial population initialization phase in metaheuristic algorithms and its role in improving the quality of initial solutions, enhancing diversity, and reducing the risk of early convergence in optimization problems, particularly in high-dimensional environments.

The lecture, presented by researcher Zainab Obaid Falah and supervised by Prof.Dr. Maitham Abu Al-Hail Shaheed, included a presentation of the proposed FPIF framework as a general, algorithm-independent framework that relies on generating candidates from multiple sources and selecting the final initial population based on quality and diversity. The researcher also reviewed the mechanism for integrating the framework with the Mountain Gazelle Optimizer algorithm, comparing it with eleven other configuration methods, and discussed the experimental results and statistical analyses that demonstrated the effectiveness of the proposed framework in improving research performance.