Hospital physician scheduling is a difficult and comprehensive procedure. It entails allocating diverse responsibilities to doctors during distinct time windows, including surgical procedures, medical facilities, and handling administrative duties. The manufacturer Specialized skill sets, and scheduling preferences have been assigned by individual physicians. The objective is to design a precisely planned program that optimizes the use of available resources and guarantees the satisfaction of physicians. Here’s when optimization methods are useful. Scholars are creating mathematical models that encompass the complexities involved in physician scheduling. Strong algorithms called meta-heuristics can be used to solve these models. Consider these algorithms as sophisticated conductors that investigate every avenue in search of the most harmonic resolution in this example, the ideal schedule. Four such conductors were investigated in this study: Genetic Algorithm (GA), Whale Optimization Algorithm (WOA), Grey Wolf Optimizer (GWO) and Particle Swarm Optimization (PSO). Their goal was to determine which conductor might produce the most optimal physician schedules while maintaining the hospital’s smooth operation, taking into account both duty obligations and preferences. Remarkably, the study showed that GA performed better in this particular scenario that the other heuristics in term of objective function.