Surrogate-assisted optimization for solving the multi-objective refrigeration system optimization problem for a 3-level refrigeration plant with economizer

In this study, the procedure of surrogate-assisted optimization is constructed to solve the multi-objective design problem of a refrigeration system. In the refrigeration process, the required coefficient of performance (COP) can be varied to the required cooling loads. In this case, the optimum operating conditions for a specified COP range is required to reduce the power consumption of the system. In this situation, the problem turns into a multi-objective optimization problem to simultaneously maximize COP and minimize power consumption. A surrogate model of the COP and power consumption are generated using several kernel functions. The best model using a linear spline kernel function is selected and used in the optimization process. A comparative study of several recent and well-known multi-objective metaheuristics was performed to measure performance of the available algorithms. The Pareto fronts containing optimum operating conditions for the refrigeration plant over the entire range of COP values were obtained in this study.