Abstract
We propose a decision-theoretic graphical model for collaborative design in a supply chain. The graphical model encodes the uncertain performance of a product resultant from an integrated design distributively. It represents preference of multiple manufacturers and end-users such that a decision-theoretic design is well-defined. We show that these distributed design information can be represented in a multiply sectioned Bayesian network. This result places collaborative design in a formal framework so that it can be subject to rigorous algorithmic study.
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References
Batill, S.M., Renaud, J.E., Gu, X.: Modeling and simulation uncertainty in multidisciplinary design optimization. In: The 8th AIAA/NASA/USAF/ISSMO Symposium on Multidisciplinary Analysis and Optimization, pp. 5–8 (2000)
Bury, K.V.: On probabilistic design. J. of Engineering for Industry, Trans of the ASME, 1291–1295 (November 1974)
Cooper, G.P.: A method for using belief networks as influence diagrams. In: Shachter, R.D., Levitt, T.S., Kanal, L.N., Lemmer, J.P. (eds.) Proc. 4th Workshop on Uncertainty in Artificial Intelligence, pp. 55–63 (1988)
Huang, S.H., Wang, G., Dismukes, J.P.: A manufacturing engineering perspective on supply chain integration. In: Proc. 10th Inter. Conf. on Flexible Automation and Intelligent Manufacturing, vol. 1, pp. 204–214 (2000)
Jensen, P.V.: An Introduction To Bayesian Networks. UCL Press, London (1996)
Keeney, R.L., Raiffa, H.: Decisions with Multiple Objectives, Cambridge (1976)
Klein, M., Sayama, H., Paratin, P., Bar-Yam, Y.: The dynamics of collaborative design: insights from complex systems and negotiation research. Concurrent Engineering Research and Applications J. 12(3) (2003)
Neapolitan, R.E.: Probabilistic Reasoning in Expert Systems. John Wiley and Sons, Chichester (1990)
Pearl, J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann, San Francisco (1988)
Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach. Prentice-Hall, Englewood Cliffs (2003)
Xiang, Y.: Probabilistic Reasoning in Multi-Agent Systems: A Graphical Models Approach. Cambridge University Press, Cambridge (2002)
Xiang, Y., Lesser, V.: On the role of multiply sectioned Bayesian networks to cooperative multiagent systems. IEEE Trans. Systems, Man, and Cybernetics-Part A 33(4), 489–501 (2003)
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Xiang, Y., Chen, J., Deshmukht, A. (2004). A Decision-Theoretic Graphical Model for Collaborative Design on Supply Chains. In: Tawfik, A.Y., Goodwin, S.D. (eds) Advances in Artificial Intelligence. Canadian AI 2004. Lecture Notes in Computer Science(), vol 3060. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24840-8_25
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DOI: https://doi.org/10.1007/978-3-540-24840-8_25
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22004-6
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