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Materials and Manufacturing Processes Volume 20, 2005 - Issue 3
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Original Articles

Comparison Between Genetic Algorithm and Genetic Programming Approach for Modeling the Stress Distribution

Miran Brezocnik Laboratory for Intelligent Manufacturing Systems, University of Maribor, Faculty of Mechanical Engineering, Maribor, SloveniaCorrespondence[email protected]
,
Miha Kovacic Laboratory for Intelligent Manufacturing Systems, University of Maribor, Faculty of Mechanical Engineering, Maribor, Slovenia
&
Leo Gusel Laboratory for Material Forming, University of Maribor, Faculty of Mechanical Engineering, Maribor, Slovenia
Pages 497-508 | Received 01 Apr 2004, Accepted 07 Sep 2004, Published online: 07 Feb 2007

Citations (20)

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Zoran Lestan, Simon Klancnik, Joze Balic & Miran Brezocnik. (2015) Modeling and Design of Experiments of Laser Cladding Process by Genetic Programming and Nondominated Sorting. Materials and Manufacturing Processes 30:4, pages 458-463.
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Miha Kovačič. (2015) Modeling of Total Decarburization of Spring Steel with Genetic Programming. Materials and Manufacturing Processes 30:4, pages 434-443.
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S Datta & P P Chattopadhyay. (2013) Soft computing techniques in advancement of structural metals. International Materials Reviews 58:8, pages 475-504.
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K. Mitra. (2008) Genetic algorithms in polymeric material production, design, processing and other applications: a review. International Materials Reviews 53:5, pages 275-297.
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N. Chakraborti. (2005) Genetic algorithms in these changing steel times. Ironmaking & Steelmaking 32:5, pages 401-404.
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Articles from other publishers (15)

Ansam A. Abdulhussien, Mohammad F. Nasrudin, Saad M. Darwish & Zaid Abdi Alkareem Alyasseri. (2023) Feature selection method based on quantum inspired genetic algorithm for Arabic signature verification. Journal of King Saud University - Computer and Information Sciences 35:3, pages 141-156.
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Ansam A. Abdulhussien, Mohammad F. Nasrudin, Saad M. Darwish & Zaid A. Alyasseri. (2023) One-Class Arabic Signature Verification: A Progressive Fusion of Optimal Features. Computers, Materials & Continua 75:1, pages 219-242.
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Kennedy C. Onyelowe, Ahmed M. Ebid, Uchenna Egwu, Michael E. Onyia, Hyginus N. Onah, Light I. Nwobia, Izuchukwu Onwughara & Ali Akbar Firoozi. (2022) Erodibility of Nanocomposite-Improved Unsaturated Soil Using Genetic Programming, Artificial Neural Networks, and Evolutionary Polynomial Regression Techniques. Sustainability 14:12, pages 7403.
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Gabriel Kronberger, Evgeniya Kabliman, Johannes Kronsteiner & Michael Kommenda. (2022) Extending a physics-based constitutive model using genetic programming. Applications in Engineering Science 9, pages 100080.
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Miha Kovačič & Uroš Župerl. (2020) Genetic programming in the steelmaking industry. Genetic Programming and Evolvable Machines 21:1-2, pages 99-128.
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Saad M. Darwish, Tamer A. Shendi & Ahmed Younes. (2019) Chemometrics approach for the prediction of chemical compounds’ toxicity degree based on quantum inspired optimization with applications in drug discovery. Chemometrics and Intelligent Laboratory Systems 193, pages 103826.
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Saad M. Darwish, Tamer A. Shendi & Ahmed Younes. (2019) Quantum‐inspired genetic programming model with application to predict toxicity degree for chemical compounds. Expert Systems 36:4.
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Shubhabrata Datta. 2016. Materials Design Using Computational Intelligence Techniques. Materials Design Using Computational Intelligence Techniques 39 63 .
P. D. Dubrovski & M. Brezocnik. (2016) Porosity and nonwoven fabric vertical wicking rate. Fibers and Polymers 17:5, pages 801-808.
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P. D. Dubrovski & M. Brezocnik. (2014) Prediction of the water absorption capacity of VIS/PES needle-punched webs using genetic algorithms. Fibers and Polymers 15:8, pages 1758-1765.
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P. D. Dubrovski & M. Brezocnik. (2012) The modelling of porous properties regarding PES/CV-blended nonwoven wipes. Fibers and Polymers 13:3, pages 363-370.
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Leo Gusel & Miran Brezocnik. (2011) Application of genetic programming for modelling of material characteristics. Expert Systems with Applications 38:12, pages 15014-15019.
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Laurent A. Baumes & Pierre Collet. (2009) Examination of genetic programming paradigm for high-throughput experimentation and heterogeneous catalysis. Computational Materials Science 45:1, pages 27-40.
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Leo Gusel & Miran Brezocnik. (2006) Modeling of impact toughness of cold formed material by genetic programming. Computational Materials Science 37:4, pages 476-482.
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S. Tiwari & N. Chakraborti. (2006) Multi-objective optimization of a two-dimensional cutting problem using genetic algorithms. Journal of Materials Processing Technology 173:3, pages 384-393.
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