MEMS Synthesis Using Stochastic Optimization

Raffi Kamalian
(Professor Alice M. Agogino --ME)

The goal of this project is to create useful, efficient design synthesis tools for MEMS devices. Design synthesis helps engineers develop rapid, optimal configurations for a given set of performance and constraint guidelines. So far, single and multi-objective genetic algorithms, as well as simulated annealing algorithms have been successfully implemented for several design synthesis examples using the SUGAR simulation tool as an engine. The research will be framed within a larger research program for developing general-purpose MEMS synthesis tools.

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