Inverse lithography technology (ILT) is one of the promising resolution enhancement techniques (RETs), as the advanced integrated circuits (IC) technology nodes still use the 193 nm light source. Among all the algorithms for ILT, the level-set-based ILT (LSB-ILT) is a feasible choice with good production result in practice. However, existing ILT algorithms optimize masks at nominal process condition without giving su?cient attention to the process variations, and thus the optimized masks show poor performance with focus and dose variations. In this paper, we put forward a new LSB-ILT algorithm for process robustness improvement with fast convergence. In order to account for the process variations in the optimization, we adopt a new form of the cost function by adding the objective function of process variation band (PV band) to the nominal cost. We also adopt the hybrid conjugate gradient (CG) method to reduce the runtime of the algorithm. We perform experiments on ICCAD 2013 benchmarks and the results show that our algorithm outperforms the top two winners of the ICCAD 2013 contest by 6.5%. We also adopt the attenuated phase shift mask (att-PSM) in the experiment with test cases from industry. The results show that our new algorithm has a fast convergence speed and reduces the process manufacturability index (PMI) by 38.77% compared with the LSB-ILT algorithm without the consideration of PV band.