Global warming is becoming a critical issue in 21st century which is mainly due to the growing rate of greenhouse gas emissions. This is mostly due to the large amount of CO2 emission from power generation activity using fossil fuels. One of the main methods of fighting global warming and reducing CO2 emission into atmosphere is to perform carbon capture, sequestration and utilization. Carbon capture can be performed through different ways, in which post combustion CO2 capture (PCC) has been developed and both economic and technically wise is in state of art. One of the disadvantages of PCC is its high efficiency penalty due to energy consumption in the reboiler for solvent regeneration. Many efforts have been done to reduce the consumption of energy in the reboiler via different strategies including process parameters optimization, solvent development and novel process configuration. This investigation used different blends of PZ and MDEA as solvent and process parameters optimization via evolutionary algorithm and multi-objective optimization. The optimization was performed on a conventional process flow diagram. CO2 capture efficiency and reboiler heat duty were used as the objective functions and main decision variables are solvent flowrate and MDEA/PZ concentration. Flue gas CO2 capture of 90, 91, 92, 93, and 94% corresponded to regeneration energy consumption of 2.68, 2.71, 2.72, 2.75, and 2.76 Eregen/tCO2; respectively. These optimized values showed a higher energy efficiency compared to MEA and MDEA/PZ in conventional process configuration.