Dr. Isack E. Kibona is a Lecturer in Mathematics and Statistics at Mbeya University of Science and Technology, Tanzania, and holds a PhD in Applied Mathematics from Central China Normal University, China. His research interests include STEM education, mathematical modelling, and operations research, with a strong focus on gender equity and inclusion in STEM. He has published research on female participation in STEM, gender equity in education, and rural STEM development. He also contributes to academic leadership, curriculum development, research supervision, and strategic planning.

AI-Assisted Simulation-Based Optimization of University Examination Halls under Space and Invigilation Resource Constraints                                                                                               Abstract: Efficientexamination planning is difficult whererooms, seats, andinvigilators are limited. This paper presents an AI-assisted simulation-based optimization framework combining digital hall modelling, periodic lattice seating, graph-based allocation, integer optimization, and MATLAB simulation. A four-level building comprises 16 halls and 8001 seats, divided equally among classes 𝐴–𝐼 (889 each) and three colour-based invigilation groups. Evaluation used a Tanzanian university session with 38 examinations and 5175 candidates. The traditional convention used 36 rooms with 7719 positions, attained 67.04% utilization, and left 2544 activated positions unused. MATLAB intlinprog assigned each examination wholly to one letter while allowing candidates to cross halls. The optimized solution activated 11 halls with 5500 positions, required 33 invigilators serving 150–168 candidates each, achieved 94.09% utilization, and reduced unused active positions to 325 while leaving five halls closed. The largest examination, with 617 candidates, was accommodated by one paired same-colour phase adjustment while preserving all letter totals. The framework therefore reduced room use and improved space and invigilation allocation while retaining periodic separation and producing seating, hall, candidate, and invigilator schedules for decision support. Keywords: Artificial Intelligence, Simulation-Based Optimization, Examination Hall Planning, Periodic Lattice Seating, Graph Coloring, Resource Allocation, Invigilation Optimization