A typical 1000 MW pressurized water reactor (PWR) nuclear power plant is considered for optimization. The thermodynamic modeling is performed based on the energy and exergy analysis, while an economic model is developed according to the total revenue requirement (TRR) method. The objective functions based on the thermodynamic and thermoeconomic analysis are obtained. The optimization process with ten degrees of freedom for plant under consideration is performed using the genetic algorithm (GA). Three levels of optimization including thermodynamic single-objective, thermoeconomic single-objective and multi-objective optimizations are performed. In multi-objective optimization, both thermodynamics and thermoeconomic objectives are considered, simultaneously. A series of optimum solutions namely as Pareto frontier are obtained. In the case of multi-objective optimization, an example of decision-making process for selection of the final optimal solution from the Pareto frontier is introduced, The results obtained using the various optimization approaches are compared and discussed. (C) 2008 Elsevier Ltd. All rights reserved.