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Product configuration systems are an emerging software technology that supports companies in deploying mass customization strategies. In this paper, we describe a CLP-based reasoning engine that we developed for a commercial configuration system. We first illustrate the advantages of the CLP approach to product configuration over other ones. Then, we describe the actual encoding of the considered product configuration problem as a constraint satisfaction problem. We devote a special attention to the key issues of constraint propagation and optimization as well as to the relevant process of assignment revision. A comparison with existing systems for product configuration concludes the paper.
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Czasopismo
Rocznik
Tom
Strony
105--133
Opis fizyczny
Bibliogr. 43 poz., tab., wykr.
Twórcy
autor
autor
autor
autor
autor
- Department of Mathematics and Computer Science, University of Udine, Italy, angelo.montanari@uniud.it
Bibliografia
- [1] Aldanondo, M., Vareilles, E.: Configuration for mass customization: how to extend product configuration towards requirements and process configuration, Journal of Intelligent Manufacturing, 19(5), 2008, 521-535.
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- [5] Asikainen, T., Männistö, T., Soininen, T.: Kumbang: A domain ontology for modeling variability in software product families, Adv. Eng. Inform., 21(1), 2007, 23-40.
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- [7] Calligaris, A., Campagna, D., De Rosa, C., Dovier, A., Montanari, A., Piazza, C.: A CLP engine for a general purpose configuration tool, in: Proc. of the 24th Italian Conference on Computational Logic (CILC) (M. Gavanelli, F. Riguzzi, Eds.), University of Ferrara, Italy, 2009.
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- [12] Frayman, F., Mittal, S.: COSSACK: A Constraint-Based Expert System for Configuration Tasks, Knowledge-Based Expert Systems in Engineering: Planning and Design, 1987, 143-166.
- [13] Freuder, E., Likitvivatanavong, C., Moretti, M., Rossi, F., Wallace, R.: Computing explanations and implications in preference-based configurators, In Barry O'Sullivan, editor, Recent Advances in Constraints, volume 2627 of LNAI, pages 76-92., 2003.
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- [22] McDermott, J. P.: R1: A rule-based configurer of computer systems, Artificial Intelligence, 19, 1982, 39-88.
- [23] McGuinness, D. L., Wright, J. R.: Conceptual modelling for configuration: A description logic based approach, Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 12(4), 1998, 333-344.
- [24] Mittal, S., Falkenhainer, B.: Dynamic Constraint Satisfaction Problems, in: Proc. of the 8th National Conference on Artificial Intelligence (AAAI), 1990, 25-32.
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- [26] Mittal, S., Frayman, F.: Towards a generic model of configuration tasks, in: Proc. of the 11th International Joint Conference on Artificial Intelligence (IJCAI), 1989, 1395-1401.
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- [34] Soininen, T., Gelle, E., Niemelä, I.: A fixpoint definition of dynamic constraint satisfaction, in: Proc. of the 5th International Conference on Principles and Practice of Constraint Programming, 1999, 419-433.
- [35] Soininen, T., Niemel, I., Tiihonen, J., Sulonen, R.: Unified configuration knowledge representation using weight constraint rules, in: Proc. of the ECAI'00 Workshop on Configuration, 2000, 79-84.
- [36] Stumptner, M., Friedrich, G., Haselbök, A.: Generative constraint based configuration of large technical systems, Artificial Intelligence for Engineering Design, Analysis and Manufacturing, 12(4), 1998, 307-320.
- [37] Subbarayan, S.: Integrating CSP Decomposition Techniques and BDDs for Compiling Configuration Problems, in: Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (R. Barták, M. Milano, Eds.), vol. 3524 of Lecture Notes in Computer Science, Springer Berlin /Heidelberg, 2005, 351-365.
- [38] Subbarayan, S., Jensen, R. M., Hadzic, T., Andersen, H. R., Hulgaard, H., M˜A¸ller, J.: Comparing Two Implementations of a Complete and Backtrack-Free Interactive Configurator, in: Proc. of CSPIA Workshop, at CP'04, 2004, 97-111.
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- [41] Tseng, H.-E., Chang, C.-C., Chang, S.-H.: Applying case-based reasoning for product configuration in mass customization environments, Expert Systems with Applications, 29(4), 2005, 913-925.
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- [43] Zheng, L., Dong, H., Vichare, P., Nassehi, A., Newman, S.: Systematic modeling and reusing of process knowledge for rapid process configuration, Robotics and Computer-Integrated Manufacturing, 24(6), 2008, 763 - 772.
Typ dokumentu
Bibliografia
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bwmeta1.element.baztech-article-BUS8-0011-0042