In this study, a mathematical model of an ice thermal energy storage (ITES) system for gas turbine cycle inlet air cooling is developed and thermal, economic, and environmental (emissions cost) analyses have been applied to the model. While taking into account conflicting thermodynamic and economic objective functions, a multi-objective genetic algorithm is employed to obtain the optimal design parameters of the plant. Exergetic efficiency is chosen as the thermodynamic objective while the total cost rate of the system including the capital and operational costs of the plant and the social cost of emissions, is considered as the economic objective. Performing the optimization procedure, a set of optimal solutions, called a Pareto front, is obtained. The final optimal design point is determined using TOPSIS decision-making method. This optimum solution results in the exergetic efficiency of 34.06% and the total cost of 28.7 million US$/y. Furthermore, the results demonstrate that inlet air cooling using an ITES systemleads to 11.63% and 3.59% improvement in the output power and exergetic efficiency of the plant, respectively. The extra cost associated with using the ITES system is paid back in 4.72 years with the income received from selling the augmented power.