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Production System Identification with Genetic Programming

Published

Author(s)

Peter O. Denno, Charles Dickerson, Jenny Harding

Abstract

Modern system identification methodologies use artificial neural nets, integer linear programming, genetic algorithms, and swarm intelligence to discover system models. Paring genetic programming, a variation of genetic algorithms, with Petri nets seems to offer attractive alternative means to discover system behaviour and structure. Yet to date, very little work has examined this pairing of technologies. Petri nets provide a grey box model of the system useful to verifying system behaviour and interpreting the meaning of operational data. Genetic programming promises a simple yet robust tool to search the space of candidate systems. Genetic programming is inherently highly parallel. This paper describes early experience with genetic programming of Petri nets to discover the best interpretation of operational data. The systems studied are serial production lines with buffers.
Conference Dates
September 5-7, 2017
Conference Location
London, UK
Conference Title
15th International Conference on Manufacturing Research

Keywords

system identification, genetic programming, Petri nets

Citation

Denno, P. , Dickerson, C. and Harding, J. (2017), Production System Identification with Genetic Programming, 15th International Conference on Manufacturing Research, London, UK, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=923277 (Accessed June 1, 2023)
Created September 6, 2017, Updated April 12, 2022