Modelling Chemical Process Systems Using a Multi-Gene Genetic Programming Algorithm

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{hinchliffe:1996:mcpsm-g,

• author = "Mark Hinchliffe and Hugo Hiden and Ben McKay and Mark Willis and Ming Tham and Geoffery Barton",
• title = "Modelling Chemical Process Systems Using a Multi-Gene Genetic Programming Algorithm",
• booktitle = "Late Breaking Papers at the Genetic Programming 1996 Conference Stanford University July 28-31, 1996",
• year = "1996",
• editor = "John R. Koza",
• pages = "56--65",
• address = "Stanford University, CA, USA",
• publisher_address = "Stanford University, Stanford, California 94305-3079, USA",
• month = "28--31 " # jul,
• publisher = "Stanford Bookstore",
• ISBN = "0-18-201031-7",
• keywords = "genetic algorithms, genetic programming",
• broken = "http://lorien.ncl.ac.uk/sorg/paper7.ps",
• 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.",
• notes = "GP-96LB MSword .ps file not compatible with unix The email address for the bookstore for mail orders is mailorder@bookstore.stanford.edu Phone no 415-329-1217 or 800-533-2670",

}

Genetic Programming entries for Mark P Hinchliffe Hugo Hiden Ben McKay Mark J Willis Ming T Tham Geoffrey W Barton

Citations