Online customization with configurable standard models

ABSTRACT

In electronic catalogs, commodities like computers and electronic equipment are specified as standard models even though a variety of possible alternative specifications can exist as a combination of selected options; therefore, customized configurations are essential to support various customers with individual needs. So the problem here is the selection of a standard model and reconfiguration with this selected model. An issue is that requirements may be fulfilled by more than one standard model. To develop an algorithm that can find the near minimum price without causing unacceptable computation effort, we devised the Standard Model Selection and Modification (SMSM) Algorithm. To establish the SMSM Algorithm, we propose the Concurrent Local Propagation procedure complemented with pruning capability owing to the nature of standard models. The effective strategies for selection of seed variables and stopping rules are devised through comparative experiments.

REFERENCES

• 1: Robin Burke, The Wasabi Personal Shopper: a case-based recommender system, Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence, p.844-849, July 18-22, 1999, Orlando, Florida, United States
• 2: Berthe Y. Choueiry , Guevara Noubir, On the computation of local interchangeability in discrete constraint satisfaction problems, Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence, p.326-333, July 1998, Madison, Wisconsin, United States
• 3: Cunningham, P., Bergmann, R., Schmitt, S., Traphöner, R. Breen, S., and Smyth, B., WEBSELL: Intelligent Sales Assistants for the World Wide Web, KI - Zeitschrift für Künstliche Intelligenz, Special Issue: Electronic Commerce Issue 1 (1) (2001) 28--32.
• 4: Gilmore, J. H., and Pine, B. J., The Four Faces of Mass Customization, Harvard Business Review (1997) 91--101.
• 5: Albert Haag, Sales Configuration in Business Processes, IEEE Intelligent Systems, v.13 n.4, p.78-85, July 1998 [doi>10.1109/5254.708436]
• 6: Gerald Hubl , Valerie Trifts, Consumer Decision Making in Online Shopping Environments: The Effects of Interactive Decision Aids, Marketing Science, v.19 n.1, p.4-21, January 2000 [doi>10.1287/mksc.19.1.4.15178]
• 7: Heinrich, M. and Jungst, E., A Resource-based Paradigm for the Configuring of Technical Systems from Modular Components, In Proceedings of Conference on Artificial Intelligence Applications, IEEE Computer Society Press, 1991, 257--264.
• 8: Daniel Hennessy , David Hinkle, Applying Case-Based Reasoning to Autoclave Loading, IEEE Expert: Intelligent Systems and Their Applications, v.7 n.5, p.21-26, October 1992 [doi>10.1109/64.163669]
• 9: Y. Huang , R. Miles, Combining case based and constraint based techniques in travel reservation systems, Proceedings of the 11th Conference on Artificial Intelligence for Applications, p.46, February 20-22, 1995
• 10: iLog, iLog Configurator White Paper, ILOG Gentilly France 2000.
• 11: iLog, iLog Optimization Suit delivering a Competitive Advantage White Paper, iLOG France May 2001.
• 12: Jacobs, S., and Kethers, S., Improving Communication and Decision Making within Quality Function Deployment, In Proceedings of Conference on Concurrent Engineering, Research and Applications, CE94, 8 1994.
• 13: Narendra Jussien , Olivier Lhomme, Local search with constraint propagation and conflict-based heuristics, Artificial Intelligence, v.139 n.1, p.21-45, July 2002 [doi>10.1016/S0004-3702(02)00221-7]
• 14: Nikos Karacapilidis , Pavlos Moraïtis, Building an agent-mediated electronic commerce system with decision analysis features, Decision Support Systems, v.32 n.1, p.53-69, November 2001 [doi>10.1016/S0167-9236(01)00100-2]
• 15: Janet Kolodner, Case-based reasoning, Morgan Kaufmann Publishers Inc., San Francisco, CA, 1993
• 16: Kolodner, J. L., and Simpson, R. L. The Mediator: Analysis of an Early Case-Based Problem Solver, Cognitive Science 13 (1989) 507--549.
• 17: Lampel, J., and Mintzberg, H., Customizing Customization, Sloan Management Review (Fall 1996) 21--30.
• 18: Hyun Jung Lee , Jae Kyu Lee, An effective customization procedure with configurable standard models, Decision Support Systems, v.41 n.1, p.262-278, November 2005 [doi>10.1016/j.dss.2004.06.010]
• 19: Lee, J. K., and Kwon, S. B., ES*: An Expert Systems Development Planner Using a Constraint and Rule-based Approach, Expert Systems with Applications 9 (2) (1995) 3--14.
• 20: Lee, K. J., Kim, H. W., Lee, J. K., Kim, T. H., Kim, C. G., Yoon, M. K., Hwang, E. J., and Park, H. J., Case and Constraint-Based Apartment Construction Project Planning System: FASTrak-APT, In Proceedings of AAAI-97, 1997, 861--866.
• 21: Lee, S. K., Lee, J. K., and Lee, K. J., Salesman Expert System for Customized Purchasing Support: UNIK-SES, Expert Systems with Applications 11 (4) (1996) 431--441.
• 22: Ian Smith , Claudio Lottaz , Boi Faltings, Spatial composition using cases: IDIOM, Proceedings of the First International Conference on Case-Based Reasoning Research and Development, p.88-97, October 23-26, 1995
• 23: Luger, G. F., and Stubblefield, W. A., Artificial Intelligence, The Benjamin/Cummings Publishing Company, Inc. 1993.
• 24: Pattie Maes , Robert H. Guttman , Alexandros G. Moukas, Agents that buy and sell, Communications of the ACM, v.42 n.3, p.81-ff., March 1999 [doi>10.1145/295685.295716]
• 25: Michael McCandless, Let's Go Shopping, IEEE Intelligent Systems, v.14 n.1, p.2-4, January 1999 [doi>10.1109/MIS.1999.747898]
• 26: Filippo Menczer , Alvaro E. Monge , W. Nick Street, Adaptive Assistants for Customized E-Shopping, IEEE Intelligent Systems, v.17 n.6, p.12-19, November 2002 [doi>10.1109/MIS.2002.1134357]
• 27: Oehler, P., Vollrath, I., Conradi, P., Bergmann, R., and Wahlmann, T., READEE - Decision Support for IP Selection using a Knowledge-Based Approach. In proceedings of IP98 Europe Proc., Miller Freeman, 1998.
• 28: Lisa Purvis , Pearl Pu, COMPOSER: A case-based reasoning system for engineering design, Robotica, v.16 n.3, p.285-295, May 1998 [doi>10.1017/S0263574798000368]
• 29: Daniel Sabin , Rainer Weigel, Product Configuration Frameworks-A Survey, IEEE Intelligent Systems, v.13 n.4, p.42-49, July 1998 [doi>10.1109/5254.708432]
• 30: Norman Sadeh , Mark S. Fox, Variable and value ordering heuristics for the job shop scheduling constraint satisfaction problem, Artificial Intelligence, v.86 n.1, p.1-41, Sept. 1996 [doi>10.1016/0004-3702(95)00098-4]
• 31: Schenner, G., and Fleischanderl, G, Modifying Configurations with Model Finding, In Proceedings of IJCAI 2003, 2003.
• 32: Sqalli, M. H., and Freuder, E. C., CBR Support for CSP Modeling of Interoperability Testing, In Proceedings of AAAI-98, Workshop on Case-Based Reasoning Integrations, Madison, Wisconsin, July 1998.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.4 INFORMATION SYSTEMS APPLICATIONS
      H.4.0 General

General Terms:
Algorithms, Design, Experimentation, Measurement, Performance

Keywords:
case-based reasoning, configuration, constraint satisfaction problem, customization