A Dimensionally-Aware Genetic Programming Architecture for Automated Innovization

Created by W.Langdon from gp-bibliography.bib Revision:1.8154

@InProceedings{conf/emo/BandaruD13,

• author = "Sunith Bandaru and Kalyanmoy Deb",
• title = "A Dimensionally-Aware Genetic Programming Architecture for Automated Innovization",
• booktitle = "Proceedings of the 7th International Conference on Evolutionary Multi-Criterion Optimization, EMO 2013",
• year = "2013",
• editor = "Robin C. Purshouse and Peter J. Fleming and Carlos M. Fonseca and Salvatore Greco and Jane Shaw",
• volume = "7811",
• series = "Lecture Notes in Computer Science",
• pages = "513--527",
• address = "Sheffield, UK",
• month = mar # " 19-22",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming, dimensional awareness, automated innovization, multi-objective optimization, design principles, NSGA-II, Matlab, GA SmallGP",
• bibdate = "2013-03-13",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/conf/emo/emo2013.html#BandaruD13",
• isbn13 = "978-3-642-37139-4",
• URL = "https://www.egr.msu.edu/~kdeb/papers/k2012015.pdf",
• URL = "http://dx.doi.org/10.1007/978-3-642-37140-0",
• DOI = "doi:10.1007/978-3-642-37140-0_39",
• size = "15 pages",
• abstract = "Automated innovization is an unsupervised machine learning technique for extracting useful design knowledge from Pareto-optimal solutions in the form of mathematical relationships of a certain structure. These relationships are known as design principles. Past studies have shown the applicability of automated innovization on a number of engineering design optimisation problems using a multiplicative form for the design principles. In this paper, we generalise the structure of the obtained principles using a tree-based genetic programming framework. While the underlying innovisation algorithm remains the same, evolving multiple trees, each representing a different design principle, is a challenging task. We also propose a method for introducing dimensionality information in the search process to produce design principles that are not just empirical in nature, but also meaningful to the user. The procedure is illustrated for three engineering design problems.",
• notes = "See also KanGAL Report Number 2012015 NB k2012015.pdf not identical to EMO 2013 publication",

}

Genetic Programming entries for Sunith Bandaru Kalyanmoy Deb

Citations