Genetic Algorithm for Optimization and Calibration in Process Simulation

Abstract

This paper proposes the use of genetic algorithms for process optimization and calibration of model parameters. The main principles of these evolution inspired optimizers are briefly explained. Afterwards, their application to two process simulation tasks is presented: (1) a layout problem in lithography processes and (2) the extraction of physical parameters of a diffusion model. The obtained results are shortly discussed.