A qualitative study on global and local optimization techniques for TCAD analysis tasks

T. Binder, C. Heitzinger, S. Selberherr

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

We compare the two well-known global optimization methods, simulated annealing and genetic optimization, to a local gradient-based optimization technique. 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 optimizer used in the experiment is based on the Levenberg-Marquardt algorithm. The actual implementation (Immin) was taken from MINPACK [1]. The genetic optimizer (genopt) is based on GALIB [2]. For the simulated annealing [3] optimizer (siman) an implementation by L. Ingber was taken. All optimizers are capable of evaluating several targets in parallel.

Original languageEnglish (US)
Title of host publication2001 International Conference on Modeling and Simulation of Microsystems - MSM 2001
EditorsM. Laudon, B. Romanowicz
Pages466-469
Number of pages4
StatePublished - 2001
Externally publishedYes
Event2001 International Conference on Modeling and Simulation of Microsystems - MSM 2001 - Hilton Head Island, SC, United States
Duration: Mar 19 2001Mar 21 2001

Publication series

Name2001 International Conference on Modeling and Simulation of Microsystems - MSM 2001

Other

Other2001 International Conference on Modeling and Simulation of Microsystems - MSM 2001
Country/TerritoryUnited States
CityHilton Head Island, SC
Period3/19/013/21/01

Keywords

  • Inverse modeling
  • Microelectronics
  • Optimization techniques
  • Semiconductors
  • Simulation

ASJC Scopus subject areas

  • General Engineering

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