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This paper illustrates a methodology developed in order to facilitate the analysis of complex systems characterized by a large number of technical, economical and environmental parameters. Thermo-economic modeling of a natural gas combined cycle including monoethanolamine absorption CO2 separation option has been integrated within a multi-objective optimizer based on a genetic algorithm in order to characterize the economic and environmental potential of such complex systems within various contexts. A natural gas combined cycle project in a district of Germany is given as a case study. The results show the influences of the configuration and technical parameter changes on the evolution of electrical efficiency of the combined cycle plant as well as on those of its sub-systems, such as gas turbine cycle and steam cycle. The optimum integrations of such a complex system under different situations are revealed by the Pareto Optimal Frontier obtained through the multi-objective optimization process, which provides information on the relationship between power generation cost and CO2 emission performances. Such information is of direct relevance for policy makers to define coherent emission tax levels, or for utility owners or project investors to choose the appropriate emission levels to be reached by the new plant, or for power generation technology suppliers to identify the market potential of their products as well as the most appropriate design for a given power unit, under given policies and economic contexts.