A dynamic multi-criteria aid for process driving using case-based reasoning;Un outil multicritère dynamique basé sur le raisonnement à partir de cas pour le pilotage des processus

Journal of Decision Systems

Volumn 18, Issue 4, 2009, Pages 459-484

  Diala, Dhouib ^a   Sid Ali, Addouche ^a   Abderrahman, El Mhamedi ^a   Habib, Chabchoub ^a  

^a NONE   (France)

Author keywords

Case based reasoning; Choquet integral; Multi criteria decision aid; Process driving

Indexed keywords

DECISION MAKING; DECISION SUPPORT SYSTEMS; INTEGRAL EQUATIONS; KNOWLEDGE ACQUISITION;

AUTOMATIC KNOWLEDGE ACQUISITION; CASEBASED REASONINGS (CBR); CHOQUET INTEGRAL; MAYR-MELNHOF PACKAGING; MULTI-CRITERIA DECISION AIDS; OPERATIONAL PROCESS; PACKING TECHNIQUES; PROCESS DECISIONS;

CASE BASED REASONING;

EID: 78650626441     PISSN: 12460125     EISSN: None     Source Type: Journal    
DOI: 10.3166/jds.18.459-484     Document Type: Article

References (37)

1. Aamodt A. and Plaza E., "Case-based reasoning: foundational issues, methodological variations and system approaches", AI Communications, Vol. 7, 1994, p. 39-59.
2. Addouche S., Dafaoui EM., El Mhamedi A., "Identification des relations entre inducteurs et indicateurs de performance des processus d'entreprise", CPI'05, Casablanca, Morocco, 2005.
3. Ahn H., Kim K-j., Han I., "A case-based reasoning system with the two-dimensional reduction technique for customer classification", Expert Systems with Applications, Elsevier Ltd., 2006 doi:10.1016/j.eswa.2006.06.021
4. Barker R.C., "Financial performance measurement: not a total solution", Management Decision, Vol. 33, No. 2, 1995, p. 31-39.
5. Cardie C., "Using decision trees to improve case-based learning", Proceedings of the tenth International Conference on machine learning, San Francisco, CA, Morgan Kaufmann, 1993, p. 25-32.
6. Cardie C. and Howe N., "Improving minority class prediction using case-specific feature weights", Proceedings of the fourteenth International Conference on machine learning, San Francisco, CA, Morgan Kaufmann, 1997, p. 57-65.
7. Cérruti O., Gattino B., Indicateurs et tableaux de bord, AFNOR Gestion, 1992.
8. Choquet G., "Théorie des capacités", Annales de l'Institut Fourier (Grenoble), Vol. 5, 1953- 1954, p. 131-295.
9. Clivillé V., Approche systémique et méthode multicritère pour la définition d'un système d'indicateurs de performance, Thèse de doctorat, Ecole Supérieure d'Ingénieurs d'Annecy, Université de Savoie, 2004.
10. Domingos P., "Context-sensitive feature selection for lazy learners" Artificial Intelligence Review, Vol. 11, No. 1-5, 1997, p. 227-253.
11. Fuchs B., Lieber J., Mille A. and Napoli A., « Réflexions sur la place du RàPC dans trois domaines de recherche actuels », Actes du 14e atelier du raisonnement à partir de cas, Besançon, mars 2006.
12. Grabisch M., Duchême J., Lino F., Perny P., "Subjective evaluation of discomfort in sitting position", Fuzzy Optimisation and Decision Making, Vol. 1, No. 3, 2002, p. 287-312.
13. Gonzalez AJ., Lingli X., Gupta UM., "Validation techniques for case-based reasoning", IEEE Trans Syst Man Cybernet-Part A: Syst Humans, Vol. 28, No. 4, 1998, p. 465-77.
14. Grabisch M. "Evaluation subjective", Concepts et Méthodes pour l'Aide à la Décision, Bouyssou D., Dubois D., Pirlot M., Prade H., Traité IC2, Hermès, 2006, p. 175-232.
15. Graham D., Smith S., "Estimating the productivity of cyclic construction operations using case-based reasoning", Advanced Engineering Informatics, Vol. 18, 2004, p. 17-28.
16. Hall M.A. "Correlation-based feature selection for discrete and numeric class machine learning", Proceedings of the 17th International Conference on machine learning, Stanford University, 2000, p. 359-366.
17. Hanney K., Keane M.T., "The adaptation knowledge: how to easy it by learning from cases", Proceedings of the Second International Conference on Case-Based Reasoning, Springer, Berlin, 1997, p. 359-370.
18. Hsu C.I., Chiu C., Hsu P.I., "Predicting information systems outsourcing success using a hierarchical design of case-based reasoning", Expert System with Application, Vol. 26, 2004, p. 435-441.
19. Jarmulak J., Craw S. and Rowe R., "Self-optimizing CBR retrieval", Proceedings of the twelfth International Conference on tools with artificial intelligence, Canada, Vancouver, 2000, p. 376-383.
20. Jiang Y-j., Chen J., Ruan X-y., "Fuzzy similarity-based rough set method for case-based reasoning and its application in tool selection", International Journal of Machine Tools and Manufacture, Vol. 46, 2006, p. 107-113.
21. Jonnson P., Lesshammar M., "Evaluation and improvement of manufacturing performance measurement systems-the role of OEE", International Journal of Operations and Production Management, Vol. 19, No. 1, 1999, p. 55-78.
22. Kolodner J. Case-based reasoning, California, Morgan Kaufmann Inc., 1993.
23. Kueng P. Krahn A.J., "Building a Process Performance Measurement System: Some Early Experiences", Journal of Scientific and Industrial Research, Vol. 58, 1999, p. 149-159.
24. Kuo R.J. Kuo Y.P. and Chen K-Y., "Developing a diagnostic system through integration of fuzzy case-based reasoning and fuzzy ant colony system" Expert Systems with Applications, Vol. 28, 2005, p. 783-797.
25. Liu DR. Ke CK., "Knowledge support for problem-solving in a production process: A hybrid of knowledge discovery and case-based reasoning", Expert Systems with Applications, 2006 Published by Elsevier Ltd.doi:10.1016/j.eswa.2006.04.026
26. Mille A., "Tutorial CBR: Etat de l'art de raisonnement à partir de cas", Plateforme AFIA'99, Palaiseau.
27. Park M.K., Lee I., and Shon K.M., "Using case reasoning for problem solving in a complex production process", Expert System with Application, Vol. 15, 1998, p. 69-75.
28. Pearson K., "On Lines and Planes of Closest Fit to Systems of Points in Space", Philosophical Magazine, Vol. 2, No, 6, 1901, p. 559-572.
29. Ravignon L., Bescos P, Joalland M., Le Bourgeois S., Maléjac A., Méthode ABC/ABM, Editions d'Organisation, 1997, p. 324.
30. Richter M.M., "Introduction", Case Based Reasoning Technology: From Foundations to Applications, Lenz, M., Bartsch-Spörl, B., Burkhardt, H.-D. and Wess, S. (Eds.), LNAI 1400, Springer, Berlin, 1988.
31. Schank R., Dynamic memory: a theory of reminding and learning in computers and people, Cambridge University Press, 1982.
32. Schank R. and Abelson R., Scripts, plans, goal and understanding, Hillsdale, NJ, Erlbaum, 1977.
33. Siedlecki W. and Sklanski J., "A note on genetic algorithms for large-scale feature selection", Pattern Recognition Letters, Vol. 10, No. 5, 1989, p. 335-347.
34. Skalak D.B., "Prototype and feature selection by sampling and random mutation hill climbing algorithms", Proceedings of the 11th International Conference on machine learning, New Brunswick, NJ, Morgan Kaufmann, 1994, p. 293-301.
35. Stearns S., "On selecting features for pattern classifiers", Proceedings of the third International Conference on Pattern Recognition, Coronado, CA, 1976, p. 71-75.
36. Tsai C-Y. and Chiu C-C., "A case-based reasoning system for PCB principal process parameter identification", Expert Systems with Applications, 2006 Published by Elsevier Ltd.doi:10.1016/j.eswa.2006.02.014
37. Watson I. "Applying case-based reasoning: techniques for enterprise systems" Comput-Aid Civil Infrastruct Engng, Vol. 13, No. 2, 1998, p. 143-50.