Adaptive optimization of noisy black-box functions inherent in microscopic models

Eddie Davis, Aditya Bindal, Marianthi Ierapetritou

Research output: Contribution to journalArticle


For stochastic systems where exact constitutive relations are unknown, a microscopic or molecular level description can be alternatively used. As microscopic simulations are computationally very expensive, there is a need for the development of robust algorithms capable of economically optimizing these noisy processes. In this paper, two approaches-an adaptive strategy using a gradient-based NLP method and a local response surface method-are applied to a stochastic reaction system. The effectiveness of these methods is evaluated in terms of the number of microscale function calls and computational time.

Original languageEnglish (US)
Pages (from-to)193-198
Number of pages6
JournalComputer Aided Chemical Engineering
Issue numberC
Publication statusPublished - Dec 1 2005


All Science Journal Classification (ASJC) codes

  • Chemical Engineering(all)
  • Computer Science Applications


  • Black-Box
  • Microscopic Models
  • Noisy Functions
  • Optimization

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