Modeling of Gelcast Ceramics using GP and Multi Objective Optimization using NSGA-II
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @Article{PUNUGUPATI:2017:MTPa,
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author = "Gurabvaiah Punugupati and Kishore Kumar Kandi and
P. S. C. Bose and C. S. P. Rao",
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title = "Modeling of Gelcast Ceramics using {GP} and Multi
Objective Optimization using {NSGA-II}",
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journal = "Materials Today: Proceedings",
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volume = "4",
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number = "8",
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pages = "8576--8586",
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year = "2017",
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note = "International Conference on Advancements in
Aeromechanical Materials for Manufacturing
(ICAAMM-2016): Organized by MLR Institute of
Technology, Hyderabad, Telangana, India",
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keywords = "genetic algorithms, genetic programming, gelcasting,
flexural strength, porosity, solid loading,
non-dominated sorting genetic algorithms-II",
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ISSN = "2214-7853",
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DOI = "doi:10.1016/j.matpr.2017.07.205",
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URL = "http://www.sciencedirect.com/science/article/pii/S221478531731502X",
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abstract = "This proposed work introduces a novel integrated
evolutionary approach and its applications for modeling
and optimization of important manufacturing process
namely gelcasting. Genetic programming (GP) is an
evolutionary algorithm which uses principle similar to
Genetic algorithms (GA) to model highly non-linear and
complex processes resulting in accurate and reliable
models. For developing models, GP method makes use of
experimental data generated from the process. For
gelcasting process input variables are solid loading,
monomer content and ratio of monomers and performance
measures are flexural strength and porosity. As the
chosen performance measures are opposite in nature,
there cannot be a single optimization solution. Hence
the problem under consideration is to be formulated as
multi objective optimization problem and solved using
NSGA-II algorithm to retrieve the Pareto optimal front.
Pareto set of process parameters in a gelcasting
process in multi objective optimization of flexural
strength porosity are obtained by executing these novel
algorithms in a single run",
- }
Genetic Programming entries for
Gurabvaiah Punugupati
Kishore Kumar Kandi
P S C Bose
C S P Rao
Citations