On the development and implementation of knowledge-driven optimisation schemes: an application in non-isothermal reactor network synthesis
Academic Article
Overview
Research
Identity
Additional Document Info
View All
Overview
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. © 2005 Elsevier B.V. All rights reserved.
published proceedings
EUROPEAN SYMPOSIUM ON COMPUTER-AIDED PROCESS ENGINEERING-15, 20A AND 20B
citation count
complete list of authors
Ashley, Victoria M||Linke, Patrick
publication date
publisher
published in
Research
keywords
Data Mining
Knowledge Driven Optimisation
Identity
Digital Object Identifier (DOI)
Additional Document Info
start page
end page
volume
issue