Binder T., Heitzinger C., Selberherr S.
Technical University Wien, AT
Keywords: inverse modeling, microelectronics, optimization techniques, semiconductors, simulation
We compare the two well-known global optimization methods, simulate annealing and genetic optimization, to a local gradient-based optimization techniques. We rate the applicability of each method in terms of the minimal achievable target value for a given number of simulation runs in an inverse modeling application. The gradient-based optimzer used in the experiment is based on the Levenberg-Marquardt algorithm. The actual implementation (llmin) was taken from MINPACK. The genetic optimzer (genopt) is based on GALIB. FOr the simulated annealing optimzer (siman) and implementation by L. Ingber was taken. All optimzers are capable of evaluating several targets in parallel.
Journal: TechConnect Briefs
Volume: 1, Technical Proceedings of the 2001 International Conference on Modeling and Simulation of Microsystems
Published: March 19, 2001
Pages: 466 - 469
Industry sector: Sensors, MEMS, Electronics
Topic: Modeling & Simulation of Microsystems
ISBN: 0-9708275-0-4