Tuning a proportional-integral-derivative (PID) controller is important to achieve the desired performance and meet design requirements in microwave heating systems. Finding optimized parameters for a PID controller is difficult using conventional methods. To overcome the problem, this study proposes to optimize the parameters of PID using the evolutionary computing (EC) approach. The type of EC approach that is implemented is particle swarm optimization (PSO). First, the study developed a microwave model with a PID controller using MATLAB and Simulink. Second, a PSO-based optimization algorithm is employed to adjust the PID controller. The performance of the microwave control system is evaluated in terms of rise time, overshoot, settling time, and steady-state error. The study also compared the performance of PSO with a type of EC optimization called a genetic algorithm (GA). The simulation results indicate that the PSO method outperforms the GA in terms of performance. The PSO obtained 2.47880, 56.881, and 61.208 for Kp, Ki, and Kd, respectively. The best method for tuning the microwave control system using PID is PSO.