Structural and flow parameters have a substantial effect on the thermal and hydraulic performance of a lithium-ion battery and cooling system. In this study, a computational fluid dynamics model is developed for double cold-plate based liquid cooling for a 20 Ah lithium-ion pouch cell, and then validated based on experimental data. An orthogonal test consisting of single factor and multi-factor analysis is designed to obtain the sensitivity of four factors, including the inlet coolant temperature, inlet coolant volume flow rate, number of cooling channels, and maximum channel width that influence the thermal behavior of the pouch cell. The multi-objective optimization for minimizing maximum temperature, maximum temperature difference and average pressure drop using genetic algorithm is conducted subjected to constraints of operating conditions for optimum battery performance. Based on the multi-objective optimization, the obtained minimized values for maximum temperature (T-max), maximum temperature difference (Delta T-max) and average pressure drop (Delta P-avg) are 25.25 degrees C, 0.22 degrees C and 48.76 kPa. The minimized objective functions are obtained at the inlet coolant temperature of 25 degrees C, inlet coolant volume flow rate of 240 mL/min, number of cooling channel of 10 and maximum channel width of 1.70 mm.