Parts produced by powder bed fusion (PBF) additive manufacturing often suffer from defects due to non-uniform temperature distribution. To address this problem, the authors have recently proposed SmartScan, an intelligent (i.e., model-based and optimization-driven) approach for generating scan sequences that substantially improve temperature uniformity. However, the current version of SmartScan can only be applied to laser scanning of simple geometric patterns with uniform-length features. This paper extends SmartScan to complex geometries with a finite set of feature lengths. Simulations and experiments involving laser marking of AISI 316L stainless steel plates demonstrate that, compared to heuristic sequences, the proposed SmartScan approach improves temperature uniformity by up to 7.95 times and reduces mean deformation by up to 1.5 times.