Abstract
Today’s configuration systems are centralized and do not allow manufacturers to collaborate online for offer-generation or sales-configuration activities. However, the integration of configurable products into the supply-chain of a business requires the cooperation of the various manufacturers’ configuration systems to jointly offer valuable solutions to customers. As a consequence, there is a need for methods that enable independent specialized agents to compute such configurations. Several approaches to centralized configuration are based on constraint satisfaction problem (CSP) solving. Most of them extend traditional CSP approaches in order to comply to the specific expressivity and dynamism requirements of configuration and similar synthesis tasks.
The distributed generative CSP (DisGCSP) framework proposed here builds on a CSP formalism that encompasses the generative aspect of variable creation and extensible domains of problem variables. It also builds on the distributed CSP (DisCSP) framework, supporting configuration tasks where knowledge is distributed over a set of agents. Notably, the notions of constraint and nogood are further generalized, adding an additional level of abstraction and extending inferences to types of variables. An example application of the new framework describes modifications to the ABT algorithms and furthermore our evaluation indicates that the DisGCSP framework is superior to classic DisCSP for typical configuration task problem encoding.
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Zanker, M., Jannach, D., Silaghi, M.C., Friedrich, G. (2008). A Distributed Generative CSP Framework for Multi-site Product Configuration. In: Klusch, M., Pěchouček, M., Polleres, A. (eds) Cooperative Information Agents XII. CIA 2008. Lecture Notes in Computer Science(), vol 5180. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85834-8_12
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