The main goal of this research is to specify the best assessment indexes for irreversible refrigeration cycles. These approaches available in the previous works are the ecological coefficient of performance and exergetic performance coefficient. Irreversible Carnot refrigerator is defined as a system. External and internal irreversibilities are included in the thermodynamic analysis. In this work, two scenarios of optimization are defined. The outcomes of each scenario are evaluated distinctly. In first scenario, in order to maximize the ecological coefficient of performance (ECOP) and exergy input to the system (E-x) and cooling load (Q(L)), multi-objective optimization algorithms have been utilized. Also, in second scenario, three objective functions comprising the ecological coefficient of performance (ECOP) and exergy input to the system (E-x) and exergetic performance criteria (EPC) are maximized concurrently via multi-objective optimization approach. Multi-objective evolutionary algorithms (MOEAs) joined with NSGA-II approach are employed throughout this paper. Three robust decision making methods including LINAMP, TOPSIS and FUZZY are employed to ascertain final solutions. Finally, error analyses of the outputs gained via decision making methods are determined.