Optimal product portfolio formulation by merging predictive data mining with multilevel optimization

Journal of Mechanical Design

Volumn 130, Issue 4, 2008, Pages

  Tucker, Conrad S ^a   Kim, Harrison M ^a  

^a UNIVERSITY OF ILLINOIS AT URBANA CHAMPAIGN   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CELL ENGINEERING; CELLULAR TELEPHONES; DATA MINING; MEMORY ARCHITECTURE; SALES;

CUSTOMER PREFERENCES; DYNAMIC DESIGN; MARKET DEMAND; MULTILEVEL OPTIMIZATION; PERFORMANCES DESIGN; PREDICTIVE DATA MINING; PREFERENCE DATA; PRODUCT ARCHITECTURE; PRODUCT FAMILIES; PRODUCT PORTFOLIOS;

PRODUCT DESIGN;

EID: 45149098757     PISSN: 10500472     EISSN: None     Source Type: Journal    
DOI: 10.1115/1.2838336     Document Type: Article

References (37)

1. Jiao, J., and Zhang, Y., 2005, "Product Portfolio Identification Based on Association Rule Mining," Comput.-Aided Des., 37(2), pp. 149-172.
2. Hsu, H., and Wang, W., 2000, "Dynamic Programming for Delayed Product Differentiation," Eur. J. Oper. Res., 156, pp. 183-193.
3. Simpson, T. W., 2004, "Product Platform Design and Custornization: Status and Promise," Artif. Intell. Eng. Des. Anal. Manuf., 18, pp. 3-20.
4. Scott, M. J., Arenillas, J., Simpson, T. W., Valliyappan, S., and Allada, V., 2006, "Towards a Suite of Problems for Comparison of Product Platform Design Methods: A Proposed Classification," Proceedings of DETC 06, 2006 ASME Design Engineering Technical Conferences, Philadelphia, PA, Paper No. DETC2006/DAC-99289.
5. Cooper, A. B., Georgiopoulos, P., Kim, H. M., and Papalambros, P. Y., 2006, "Analytical Target Setting: An Enterprise Context in Optimal Product Design," ASME J. Mech. Des., 128(1), pp. 4-13.
6. Kim, H. M., Michelena, N. F., Papalambros, P. Y., and Jiang, T., 2003, "Target Cascading in Optimal System Design," ASME J. Mech. Des., 125(3), pp. 474-480.
7. de Weck, O., Sub, E., and Chang, D., 2003, "Product Family and Platform Portfolio Optimization," Proceedings of DETC03, 2003 ASME Design Engineering Technical Conferences, Chicago, II, Paper No. DETC03/DAC-48721.
8. Gonzales-Zugasti, J. P., Otto, K. N., and Baker, J. D., 2001, "Assessing Value in Platformed Product Family Design," Res. Eng. Des., 13(1), pp. 30-41.
9. Desai, P., Kekre, S., Radhakrishnan, S., and Srinivasan, K., 2001, "Product Differentiation and Commonalityin Design: Balancing Revenue and Cost Drivers," Manage. Sci., 47(1), pp. 37-51.
10. Kim, K., and Chhajed, D., 2000, "Commonality in Product Design: Cost Saving, Valuation Change and Cannibalization," Eur. J. Oper. Res., 125(3), pp. 602-621.
11. Agard, B., and Kusiak, A., 2004, "Data Mining Based Methodology for the Design of Product Families," Int. J. Prod. Res., 42(15), pp. 2955-2969.
12. Moon, S. K., Kumara, S. R. T., and Simpson, T W., 2006, "Data Mining and Fuzzy Clustering to Support Product Family Design," Proceedings of DETC 06, 2006 ASME Design Engineering Technical Conferences, Philadelphia, PA, Paper No. DETC2006/DAC-99287.
13. 2002, Data Mining for Design and Manufacturing, Dan Braha, ed., Springer.
14. McEntire, J., 2003, D2K Toolkit User Manual, National Center for Supercomputing Applications (NCSA).
15. Cook H. E., 1997, Product Management: Value, Quality, Cost, Price, Profit, and Organization, Chapman and Hall, London.
16. Dean, D. H., 2004, "Evaluating Potential Brand Associations Through Conjoint Analysis and Market Simulation," J. Product Brand Management, 13(7), pp. 506-513.
17. Rish, I., 2001, "An Empirical Study of the Naive Bayes Classifier," IJCAI 2001 Workshop on Empirical Methods in Artificial Intelligence.
18. Zhang, H., Ling, C., and Zhao, Z., 2000, "The Learnability of Naive Bayes," Canadian AI2000, LNAI 1822, pp. 432-441.
19. Meretakis, D., and Wuthrich, B., 1999, "Extending Naive Bayes Classifiers Using Long Itemsets," Fifth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 164-174.
20. Flack, P. A., and Lachiche, N., 2004, "Naïve Bayes Classification of Structured Data," Mach. Learn., 57(3), pp. 233-269.
21. Kleinberg, E. M., 2000, Lecture Notes in Computer Science, Springer, Berlin, Vol. 1857.
22. Degroot, M., 1970, Optimal Statistical Decisions, McGraw-Hill, New York.
23. Sparacino, G., Tombolato, C., and Cobefli, C., 2000, "Maximum-Likelihood Versus Maximum a Posteriori Parameter Estimation of Physiological System Models: The c-Peptide Impulse Response Case Study," IEEE Trans. Biomed. Eng., 47(6), pp. 801-811.
24. Fayyad, U. and Uthurusamy, R., 2007, "Data Mining and Knowledge Discovery in Databases," Communications of the ACM, 39(11), p. 24(3).
25. Tucker, C., and Kim, H. M., 2006, "Cell Phone Customer Survey: Online Interactive User Interface Created Using Webtools," https:// webtools.uiuc.edu/survey/Secure?id=5617516.
26. Boulicaut, J., Esposito, F., Giannotti, F., and Pedreschi, D., 2004, Knowledge Discovery in Databases: PKDD 2004, Springer, New York.
27. Campos, M., Stengard, P., and Milenova, B., 2005, "Data-Centric Automated Data Mining," Fourth International Conference on Machine Learning and Applications.
28. Holmstrom, K., Goran, A. O., and Edvall, M. M., 2006, Users Guide for TOMLAB/MINLP, Tomlab Optimization, Tomlab Optimization Inc.
29. Kim, H. M., Rideout, D. G., Papalambros, P. Y., and Stein, J. L., 2003, "Analytical Target Cascading in Automotive Vehicle Design," ASME J. Mech. Des., 125(3), pp. 481-489.
30. Canback, D., 2003, "Diseconomies of Scale in Large Corporations," Technical description, Canback Dangel Predictive Analytics Advisors, 10 Derne Street, Boston, MA 02114.
31. Milliken and Company, 2006, "Cost Savings Benefit of Manufacturing," private communication.
32. Cell Phone Battery Warehouse. Standby and talk times. 2006, http:// www.batteries4less.com/.
33. Neuvo, Y. 2004, "Cellular Phones as Embedded Systems," IEEE International Solid-State Circuits Conference.
34. Buchmann, I., 1999, "Battery Mystery Solved: Why Batteries for Digital Cell Phones Fail," Batteries Conference on Applications and Advances, pp. 359-362.
35. Klepper, M., Miller, P., and Miller, L., 2003, "Advanced Display Technologies, Printing Industry Center at Rochester Institute of Technology (RIT).
36. 1999, The Math Works, Inc., Natick, MA, Optimization Toolbox for Use with MATLAB, version 2.
37. Berry, S., and Pakes, A., 2007, "The Pure Characteristics Demand Model," International Economic Review, 48(4), pp. 1193-1225