Abstract-The spectrum sensing, multi-optimization (SS-MO) technique was recently investigated to enhance radar performance when the radar operates in the presence of radio frequency interference (RFI). The SS-MO technique passively monitors the operating band of the radar using spectrum sensing to identify a frequency sub-band with minimal RFI, thus allowing the radar to maintain a high signal to inference plus noise ratio (SINR). Prior results have indicated significant improvement of SINR and PSLR (peak to average sidelobe level ratio) at the cost of a high computational complexity. In this paper, the non-dominated sorting genetic algorithm II (NSGA-II) is used to lower the computational complexity while maintaining performance.