ExamPlanner: Examination Seating and Faculty Duty Management System

Manual coordination of university examinations and cheating which directly hurts the core integrity of educational testing. To avoid these problems modern computer-driven frameworks usually separate the problem into isolated tasks handling student layouts and faculty assignments as independent steps. Approximate metaheuristics such as Genetic Algorithms, Simulated Annealing or simple greedy selection methods are common because these resource problems are mathematically classified as polynomial-time hard (NP-hard) complexities [10]. But approximate heuristics have academic limits: they react strongly to the first parameters often get stuck, in local optima and give no mathematical promise of perfect optimality [2]. As a result institutions must accept resource schedules that're not optimal that frequently clash with employee availability windows and that do not separate branch peers effectively [2]. This research presents ExamPlanner, an optimization framework that handles student seating layouts and faculty duty scheduling at the same time. Unlike methods that use stochastic searching ExamPlanner turns institutional policies directly into an exact mathematical model solved by Google OR-Tools' CP-SAT constraint programming solver [2]. The system runs on a cloud-native Supabase (PostgreSQL) database that keeps full relational data models across university branches and departments. Importantly the platform adds a dynamic "Algorithmic Critique" interaction mechanism [2]. This engine stops manual administrator layout changes through a web interface. Checks them against the live constraint matrix instantly moving from automated guessing to a reliable human-in-the-loop validation process [2].