On the development and implementation of knowledge-driven optimisation schemes

an application in non-isothermal reactor network synthesis

Victoria M. Ashley, Patrick Linke

Research output: Contribution to journalArticle

Abstract

Knowledge driven optimisation has been developed in an attempt to overcome difficulties in applying existing reactor network synthesis methods to complex systems. Knowledge derived from kinetic relationships is applied to superstructure optimisation in the form of a customised rule-based Tabu Search where rules are used to guide optimisation decisions. Nonisothermal behaviour is represented using temperature profiles along the length of a reactor. Results show the method outperforms a standard Tabu Search both in solution quality and speed of convergence.

Original languageEnglish
Pages (from-to)175-180
Number of pages6
JournalComputer Aided Chemical Engineering
Volume20
Issue numberC
DOIs
Publication statusPublished - 2005
Externally publishedYes

Fingerprint

Tabu search
Large scale systems
Kinetics
Temperature

Keywords

  • data mining
  • Knowledge driven optimisation

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Computer Science Applications

Cite this

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