Includes bibliographical references.

The Darwin's theory of natural evolution is being used in the last one decade for optimization of many engineering systems in the name of genetic algorithms. In the present paper, genetic algorithms are used for the optimization of the gas turbine cycles. Based on thermodynamic consideration of a gas turbine plant, the pressure ratio is optimized with genetic algorithms for maximum efficiency or maximum net power density. In addition to the pressure ratio, component efficiencies and maximum cycle temperature are treated as independent (decision) variables. The effects of the independent variables on the pressure ratio are also determined. Economics are combined with thermodynamics to formulate a thermoeconomic optimization problem. The results obtained by genetic algorithms are compared with the numerical results to demonstrate the capability of genetic algorithms in carrying out an optimization of thermodynamic cycles for gas turbines.