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Optimization Methods for Inventive Design

  • Lei Lin
  • Ivana RasovskaEmail author
  • Roland De Guio
  • Sébastien Dubois
Chapter

Abstract

The work presented in this chapter deals with problems of invention where solutions of optimization methods do not meet the objectives of problems to solve. The problems previously defined exploit, for their resolution, a problem extending the model of classical TRIZ in a canonical form called “generalized system of contradictions.” This research draws up a resolution process based on the simulation-optimization-invention loop using both solving methods of optimization and invention. More precisely, it models the extraction of generalized contractions from simulation data as combinatorial optimization problems and offers algorithms that provide all the solutions to these problems. In addition, it provides heuristics to select variables and their relevant values involved in generalized contradictions and/or useful for optimization. The contributions concern theory and practice of the inventive design. The work also explores cross-fertilization between optimization and TRIZ.

Keywords

TRIZ Inventive design Optimization Contradiction analysis 

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References

  1. Altshuller GS (1985) Algorithm of inventive problem solving. http://www.evolocus.com/textbooks/ariz85c.pdf. Accessed 3 Feb 2016
  2. Bonnardel N (2000) Understanding and supporting creativity in design. Knowl Based Syst 13:505–513CrossRefGoogle Scholar
  3. Brohm J-M (2003) Les principes de la dialectique. Editions de la PassionGoogle Scholar
  4. Cameron G (2015) ARIZ explored: a step-by-step guide to ARIZ the algorithm for solving inventive problems. Createspac, Charleston, SCGoogle Scholar
  5. Collette Y, Siarry P (2004) Multiobjective optimization: principles and case studies. Springer, New YorkCrossRefzbMATHGoogle Scholar
  6. Dash M, Liu H (1997) Feature selection for classification. Intell Data Anal 1:131–156CrossRefGoogle Scholar
  7. Doreian P (1999) An intuitive introduction to blockmodeling with examples. Bull Méthodol Soc 61:5–34. doi: 10.1177/075910639906100103 CrossRefGoogle Scholar
  8. Dubois S, Eltzer T, De Guio R (2009a) A dialectical based model coherent with inventive and optimization problems. Comput Ind 60:575–583. doi: 10.1016/j.compind.2009.05.020 CrossRefGoogle Scholar
  9. Dubois S, Rasovska I, De Guio R (2009b) Towards an automatic extraction of generalized system of contradictions out of solutionless design of experiments. In: 3nd IFIP working conference on computer aided innovation (CAI): growth and development of CAI, pp 70–79Google Scholar
  10. Dubois S, De Guio R, Rasovska I (2011) Different ways to identify generalized system of contradictions, a strategic meaning. Proc Eng 9:119–125. doi: 10.1016/j.proeng.2011.03.105 CrossRefGoogle Scholar
  11. Eltzer T, DeGuio R (2007) Constraint based modelling as a mean to link dialectical thinking and corporate data. application to the design of experiments. In: León-Rovira N (ed) Trends in computer aided innovation: second IFIP working conference on computer aided innovation, Michigan, USA, 8–9 October 2007. Springer, Boston, pp 145–155Google Scholar
  12. Gano DL (2001) Effective problem solving: a new way of thinking. In: Annual quality congress proceedingsGoogle Scholar
  13. Guyon I (2003) An introduction to variable and feature selection. J Mach Learn Res 3:1157–1182zbMATHGoogle Scholar
  14. Guyon I, Weston J, Barnhill S, Vapnik V (2002) Gene selection for cancer classification using support vector machines. Mach Learn 46:389–422CrossRefzbMATHGoogle Scholar
  15. Jain A, Murty M, Flynn PJ, Rosenfeld A, Bowyer K, Ahuja N, Jain A (1999) Data clustering: a review. ACM Comput Surv 31:264–323CrossRefGoogle Scholar
  16. Khomenko N, De Guio R (2007) OTSM network of problems for representing and analysing problem situations with computer support. In: Trends in computer aided innovation. 2nd IFIP working conference on computer aided innovation. Technical Center Brighton, Springer, pp 77–88Google Scholar
  17. Lewis DD, Ringuette M (1994) A comparison of two learning algorithms for text categorization. Proc SDAIR 81–93Google Scholar
  18. Liiv I (2010) Seriation and matrix reordering methods: an historical overview. Stat Anal Data Min. doi: 10.1002/sam.10071
  19. Lin L (2016) Optimization methods for inventive design. PhD dissertation, University of StrasbourgGoogle Scholar
  20. Lin L, Rasovska I, De Guio R, Dubois S (2013) Algorithm for identifying generalized technical contradictions in experiments. J Eur Syst Autom 47(4–8):563–588. doi: 10.3166/jesa.47.563-588 Google Scholar
  21. Lin L, Dubois S, De Guio R, Rasovska I (2015) An exact algorithm to extract the generalized physical contradiction. Int J Interact Des Manuf 9:185–191CrossRefGoogle Scholar
  22. Liu H, Motoda H (1998) Feature selection for knowledge discovery and data mining. Kluwer Academic Publishers, New YorkCrossRefzbMATHGoogle Scholar
  23. Rasovska I, Dubois S, De Guio R (2010) Study of different principles for automatic identification of generalized system of contradiction out of design of experiments. In: 8th international conference of modeling and simulation, Hammamet, TunisGoogle Scholar
  24. Saeys Y, Inza I, Larrañaga P (2007) A review of feature selection techniques in bioinformatics. Bioinformatics 23:2507–2517. doi: 10.1093/bioinformatics/btm344 CrossRefGoogle Scholar
  25. Sève L (1998) Nature, science, dialectique: un chantier à rouvrir. In: Sève L (ed) Sciences et dialectiques de la nature. Éditions L, pp 23–247Google Scholar
  26. Sève L, Guespin-Michel J (2005) Émergence, complexité et dialectique: sur les systèmes dynamiques non linéaires. Éditions, ParisGoogle Scholar
  27. Shlens J (2014) A tutorial on principal component analysis. Int J Remote Sens 51Google Scholar
  28. Yang Y, Pedersen JO (1997) A comparative study on feature selection in text categorization. Mach Learn Work Then Conf 412–420. doi: 10.1093/bioinformatics/bth267

Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Lei Lin
    • 1
  • Ivana Rasovska
    • 2
    Email author
  • Roland De Guio
    • 1
  • Sébastien Dubois
    • 1
  1. 1.National Institute of Applied SciencesStrasbourgFrance
  2. 2.University of Strasbourg, IUT de HaguenauHaguenauFrance

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