This paper studies a comparison of optimization algorithms to enhance temperature control method of thermal vacuum chamber (TVC) for satellite testing. The gaseous nitrogen (GN2) is used in TVC to control the temperature requirement and proportional integral derivative (PID) controller is adopted in order to realize it. However, the temperature profile is fluctuated and more time is needed before it managed to achieve the temperature set point. Therefore, a study is done to identify the algorithms that can be applied to optimize the temperature control system of TVC. The study is aim to improve the current temperature control in terms of settling time and overshoot. The method used in the review is by comparing the optimization algorithms that have been used to optimize the temperature control system. The study will be done using other related works that had been done by other researchers. From the review that has been done, the genetic algorithm (GA) is believed to be the best method that can be implemented into the temperature control system of TVC. In the future, the study will further analyse by using simulation tools and real time data generated by the TVC.