Abstarct: Shortages in fossil fuels along with increased environmental contaminations incurred by their consumption indicate the importance of implementing renewable resources of energy such as solar energy. With suitable circumstances in terms of solar radiation and numerous combined cycle power plants all around the country, Iranian territory provides adequate basis for using for integrated solar combined cycle power plant as a suitable solution. In the present dissertation, design parameters of an integrated solar combined cycle power plant were optimized, using genetic algorithm, in two well-determining parts, namely the solar field and the HRSG, so as to reduce investment cost and enhance the power output. Aimed at simulating operation cycle of Damavand Power Plant, as a case study, cycle components were thermodynamically modelled using matlab software. Once the written code was validated, considering the bi-pressure nature of the HRSG under study, two scenarios were considered for integrating the solar field with the HRSG. The first scenario was to connect the solar field to the high pressure end of the HRSG, and the second scenario was to connect the solar field to the low pressure end of the HRSG. Analyzing the obtained results, the second scenario was found to be capable of producing an extra 3.1 MW output power at lower cost by 900,000 USD, as compared to the first scenario. Finished with evaluating the scenarios and choosing the optimum one, HRSG and solar field design parameters were optimized, so that the power output was raised by 16.8 MW while reducing the associated cost with the recovery boiler design by 1,100,000 USD. In the case of solar field, genetic algorithm optimization gave 5,100,000 USD reduction in the field construction costs while reducing the power loss by 1.3 MW. Therefore, one can say that the genetic algorithm succeeded to provide optimum values of design parameters, so as to achieve a combination of the lowest cost with the maximum power output.