Modeling and solving technical product configuration problems

Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM

Volumn 25, Issue 2, 2011, Pages 115-129

  Falkner, Andreas ^a   Haselböck, Alois ^a   Schenner, Gottfried ^a   Schreiner, Herwig ^a  

^a SIEMENS AG ÖSTERREICH   (Austria)

Author keywords

Artificial Intelligence; Constraint Logic Programming; Constraint Satisfaction; Product Configuration; SAT

Indexed keywords

ARTIFICIAL INTELLIGENCE METHODS; CONSTRAINT LOGIC PROGRAMMING; CONSTRAINT SATISFACTION; PRODUCT CONFIGURATION; PRODUCT CONFIGURATOR; SAT; TECHNICAL PRODUCTS;

ARTIFICIAL INTELLIGENCE; COMPUTER PROGRAMMING LANGUAGES; LOGIC PROGRAMMING;

SOFTWARE ARCHITECTURE;

EID: 79956106296     PISSN: 08900604     EISSN: 14691760     Source Type: Journal    
DOI: 10.1017/S0890060410000570     Document Type: Conference Paper

References (24)

1. Albert, P., Henocque, L., & Kleiner, M. (2008). Ant colony optimization for configuration. Proc. 20th IEEE Int. Conf. Tools With Artificial Intelligence, pp. 247-254.
2. Baader, F., McGuinness, D.L., Nardi, D.,& Patel-Schneider, P.F. (2003). The Description Logic Handbook. Cambridge: Cambridge University Press.
3. Cooper, M., Jeavons, P., & Salamon, A. (2008). Hybrid tractable CSP's which generalize tree structure. Proc. ECAI, pp. 530-534.
4. Dechter, R., & Meiri, I. (1989). Experimental evaluation of preprocessing techniques in constraint satisfaction problems. Proc. 11th IJCAI, pp. 271-277.
5. Eiter, T., Gottlob, G., & Mannila, H. (1997). Disjunctive datalog. ACM Transactions on Database Systems 22/3, 315-363.
6. Falkner, A., Feinerer, I., Salzer, G., & Schenner, G. (in press). Computing product configurations via UML and integer linear programming. International Journal on Mass Customization.
7. Falkner, A., & Haselböck, A. (2009). A simple evaluation process for configurability. Proc. IJCAI-09 Workshop on Configuration, pp. 17-22.
8. Felfernig, A. (2007). Standardized configuration knowledge representations as technological foundation for mass customization. IEEE Transactions on Engineering Management 54(1), 41-56. (Pubitemid 46431427)
9. Felfernig, A., Friedrich, G., Jannach, D., Stumptner, M., & Zanker, M. (2003). Configuration knowledge representations for Semantic Web applications. Artificial Intelligence for Engineering Design, Analysis and Manufacturing 17(1), 31-50.
10. Felfernig, A., Friedrich, G., Jannach, D.,& Zanker, M. (2002). Configuration knowledge representation using UML/OCL. Proc. 5th Int. Conf. Unified Modeling Language, pp. 49-62. Berlin: Springer-Verlag.
11. Fleischanderl, G., Friedrich, G., Haselböck, A., Schreiner, H., & Stumptner, M. (1998). Configuring large-scale systems with generative constraint satisfaction. IEEE Intelligent Systems 13(4), 59-68. (Pubitemid 128574933)
12. Frühwirth, T. (2008). Welcome to constraint handling rules. In Constraint Handling Rules-Current Research Topics (Schrijvers, T., & Frühwirth, T., Eds.), L Vol. 5388. New York: Springer-Verlag.
13. Gent, I.P., Petrie, K.E., & Puget, J. (2006). Symmetry in constraint programming. In Handbook of Constraint Programming (Rossi, F., van Beek, P., & Walsh, T., Eds.), pp. 329-376. Amsterdam: Elsevier.
14. Goldberg, D.E. (1989). Genetic Algorithms in Search, Optimization & Machine Learning. Reading, MA: Addison-Wesley Professional.
15. Gottlob, G., Greco, G.,& Mancini, T. (2007). Conditional constraint satisfaction: Logical foundations and complexity. Proc. IJCAI 2007, pp. 88-93.
16. Jackson, D. (2002). Alloy: A lightweight object modeling notation. ACM Transactions on Software Engineering Methodologies 112, 256-290. (Pubitemid 44159313)
17. Khichane, M., Albert, P., & Solnon, C. (2008). Integration of ACO in a constraint programming language. Proc. ANTS, pp. 84-95.
18. Kirkpatrick, S., Gelatt, C.D., Jr., & Vecchi, M.P. (1983). Optimization by simulated annealing. Science 220(4598), 671-680.
19. Mayer,W., Bettex, M., Stumptner, M., Falkner, A.,& Faltings, B. (2009). On solving complex rack configuration problems using CSP methods. Proc. IJCAI-09 Workshop on Configuration, pp. 53-60.
20. McDermott, J. (1982). R1: A rule-based configurer of computer systems. Artificial Intelligence 19, 39-88.
21. Michalewicz, Z., & Fogel, D.B. (2004). How to Solve It: Modern Heuristics. Berlin: Springer.
22. Sabin, D., & Weigel, R. (1998). Product configuration frameworks-a survey. IEEE Intelligent Systems 13(4), 42-49. (Pubitemid 128574931)
23. Schoofs, L., & Naudts, B. (2000). Solving CSPs with ant colonies. Proc. ANTS, 2000.
24. Torlak, E. (2009). A constraint solver for software engineering: Finding models and cores of large relational specifications. PhD Thesis. MIT.