Fast simulated diffusion: an optimization algorithm for multiminimum problems and its application to MOSFET model parameter extraction

An optimization method, called fast simulated diffusion (FSD), is proposed to solve a multiminimial optimization problem on multidimensional continuous space. The algorithm performs a greedy search and a random search alternately and can find the global minimum with a practical success rate. An efficient hill-descending method employed as the greedy search in the FSD is proposed. When the FSD is applied to a set of standard test functions, it shows an order of magnitude faster speed than the conventional simulated diffusion. Some of the optimization problems encountered in system and VLSI designs are classified into multioptimal problems. The proposed FSD is successfully applied to a MOSFET parameter extraction problem with a deep submicron MOSFET.<
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