Inproceedings,
Modelling Chemical Process Systems Using a Multi-Gene Genetic Programming Algorithm
Late Breaking Papers at the Genetic Programming 1996 Conference Stanford University July 28-31, 1996, page 56--65. Stanford University, CA, USA, Stanford Bookstore, (28--31 July 1996)
Abstract
In this contribution a multi-gene Genetic Programming
(Gp) Algorithm is used to evolve input output models of
chemical process systems. Three case studies are used
to demonstrate the performance of the method when
compared to a standard GP algorithm. A statistical
analysis procedure is used to aid in the assessment of
the results and suggest the number of independent runs
required to obtain a successful result. It is concluded
that the multi-gene algorithm provides superior
performance, as partitioning the problem into
sub-groups incorporates basic heuristic knowledge of
the search space.
