Global optimisation of source and mask in inverse lithography via tabu search combined with genetic algorithm

Abstract

Source mask optimisation (SMO) is a resolution enhancement technology that is utilised in the advanced process node of optical lithography to achieve acceptable imaging quality and fidelity. It is crucial in enhancing the convergence performance and optimisation capability of pixel-based SMO. In this study, an SMO approach that employs a genetic algorithm (GA), combined with the tabu search method (TS), is proposed. GA-TS, a hybrid-type global optimisation algorithm, has an outperforming capacity to avoid local optima owing to the excellent local searching function of TS. Furthermore, an edge-optimisation strategy was implemented to optimise the mask for a low-complexity mask layout. The simulation results confirm that the proposed approach exhibits exceptional optimisation capability and convergence performance.