Stochastic Optimization Framework (SOF) for computer-optimized design, engineering, and performance of multi-dimensional systems and processes

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

10 Scopus citations

Abstract

Many systems and processes, both natural and artificial, may be described by parameter-driven mathematical and physical models. We introduce a generally applicable Stochastic Optimization Framework (SOF) that can be interfaced to or wrapped around such models to optimize model outcomes by effectively "inverting" them. The Visual and Autonomous Exploration Systems Research Laboratory (http://autonomy.caltech.edu) at the California Institute of Technology (Caltech) has long-term experience in the optimization of multi-dimensional systems and processes. Several examples of successful application of a SOF are reviewed and presented, including biochemistry, robotics, device performance, mission design, parameter retrieval, and fractal landscape optimization. Applications of a SOF are manifold, such as in science, engineering, industry, defense & security, and reconnaissance/exploration.

Original languageEnglish (US)
Title of host publicationSpace Exploration Technologies
DOIs
StatePublished - 2008
Externally publishedYes
EventSpace Exploration Technologies - Orlando, FL, United States
Duration: Mar 17 2008Mar 18 2008

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6960
ISSN (Print)0277-786X

Other

OtherSpace Exploration Technologies
CountryUnited States
CityOrlando, FL
Period3/17/083/18/08

Keywords

  • Degeneracy
  • Design/performance optimization
  • Fitness function
  • Global minimum
  • Gradient-based steepest-descent methods
  • Local minima
  • Multi-parameter optimization
  • Overlap parameter distribution
  • Simulated annealing
  • Stochastic optimization framework

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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