Competitive advantages of evolutionary computation for industrial applications

2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005. Proceedings

Volumn 1, Issue , 2005, Pages 166-173

  Kordon, A K ^a   Kalos, A N ^a   Castillo, F A ^a   Kotanchek, M E ^b   Jordaan, E M ^c   Smits, G F ^c  

^a DOW CHEMICAL COMPANY   (United States)

^b Evolved Analytics   (United States)

^c DOW BENELUX B V   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

EMULATORS; INFERENTIAL SENSORS; MECHANISTIC MODELS; SUPPORT VECTOR MACHINES;

COMPETITION; LEARNING SYSTEMS; MARKETING; NEURAL NETWORKS; OPTIMIZATION; PRODUCT DEVELOPMENT; RESEARCH AND DEVELOPMENT MANAGEMENT; STATISTICAL METHODS;

EVOLUTIONARY ALGORITHMS;

EID: 27144516373     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (22)

1. I. Parmee, Evolutionary and Adaptive Computing in Engineering Design, London, UK: Springer, 2001.
2. C. M. Christensen, S. D. Anthony, and E. A. Roth, Seeing What's Next, Boston, MA: Harvard Business School Press, 2004.
3. S. Bharadwaj, P. Varadarajan, and J. Fahy, "Sustainable Competitive Advantage in Service Industries: A Conceptual Model and Research Propositions." Journal of Marketing, vol. 57 (10), pp. 83-99, 1993.
4. L. Jain and N. Martin (Editors), Fusion of Neural Networks, Fuzzy Sets, and Genetic Algorithms: Industrial Applications, Boca Raton, FL: CRC Press, 1999.
5. M. Kotanchek, A. Kordon, G. Smits, F. Castillo, R. Pell, M.B. Seasholtz, L. Chiang, P. Margl, P.K. Mercure, A. Kalos, "Evolutionary Computing in Dow Chemical", In Proceedings of GECCO'2002, New York, volume Evolutionary Computation in Industry, pp. 101-110, 2002.
6. A. Kordon, F. Castillo, G. Smits, and M. Kotanchek, "Application Issues of Genetic Programming in Industry", In: T. Yu, R. Riolo and B. Worzel (eds): Genetic Programming Theory and Practice III. Springer, New York, NY, pp. xx , 2005.
7. A. Kordon, A. Kalos, and B. Adams, "Empirical Emulators for Process Monitoring and Optimization", In Proceedings of the IEEE 11th Conference on Control and Automation MED'2003, Rhodes, Greece, pp.111, 2003.
8. A. Kordon, G. Smits, A. Kalos, and E. Jordaan, "Robust Soft Sensor Development Using Genetic Programming", In Nature-Inspired Methods in Chemometrics, (R. Leardi-Editor), Amsterdam: Elsevier, 2003.
9. R. Neelakantan and J. Guiver,"Applying Neural Networks", Hydrocarb Proc, vol. 9 (1), pp.114-119, 1998.
10. J. Koza, Genetic Programming: On the Programming of Computers by Means of Natural Selection, Cambridge, MA: MIT Press, 1992.
11. W. Banzahf, P. Nordin, R. Keller, and F. Francone, Genetic Programming: An Introduction, San Francisco, CA: Morgan Kaufman, 1998.
12. G. Smits and M. Kotanchek,"Pareto-Front Exploitation in Symbolic Regression", Genetic Programming Theory and Practice II, pp 283-300, U.M. O'Reilly, T. Yu, R. Riolo and B. Worzel (Eds), Boston, MA:Springer, 2004.
13. A. Kordon, E. Jordaan, L. Chew, G. Smits, T. Bruck, K. Haney, and A. Jenings, "Biomass Inferential Sensor Based on Ensemble of Models Generated by Genetic Programming", In Proceedings of GECCO 2004, Seattle, WA, pp. 1078-1089, 2004.
14. F. W. Breyfogle III, Implementing Six Sigma, 2nd ed., Hoboken, NJ: Wiley, 2003.
15. A. Kordon and G. Smits, "Soft Sensor Development Using Genetic Programming", In Proceedings of GECCO'2001, San Francisco, CA, pp. 1346 - 1351, 2001.
16. J. Joseph and C. Fellenstein, Grid Computing, Englewood Cliffs, NJ: Prentice Hall, 2003.
17. A. Kordon, G. Smits, E. Jordaan, and E. Rightor, "Robust Soft Sensors Based on Integration of Genetic Programming, Analytical Neural Networks, and Support Vector Machines", In Proceedings of WCCI 2002, Honolulu, pp. 896 - 901, 2002.
18. V. Vapnik, The Nature of Statistical Learning Theory, 2nd ed, New York, NY: Springer, 2000.
19. F. Castillo, A. Kordon, J. Sweeney, and W. Zirk, "Using Genetic Programming in Industrial Statistical Model Building", In: O'Raily U. , Yu T., Riolo, R. and Worzel, B. (eds): Genetic Programming Theory and Practice II. New York, NY: Springer, pp. 31 - 48, 2004.
20. A. Kordon, H. Pham, C. Bosnyak, M. Kotanchek, and G. Smits, "Accelerating Industrial Fundamental Model Building with Symbolic Regression: A Case Study with Structure - Property Relationships", In Proceedings of GECCO'2002, New York, volume Evolutionary Computation in Industry, pp. 111-116, 2002.
21. S. Katare, A. Kalos, and D. West, "A Hybrid Swarm Optimizer for Efficient Parameter Estimation", In Proceedings of CEC'2004, Portland, OR, pp. 309-315, 2004.
22. G. Smits, personal communication, 2005.