Abstract
Today’s configurators are centralized systems and do not allow manufacturers to cooperate on-line for offer-generation or sales-configuration. However, supply chain integration of configurable products requires the cooperation of the configuration systems from the different manufacturers that jointly offer solutions to customers. As a consequence, there is a high potential for methods that enable the computation of such configurations by independent specialized agents. Several approaches to centralized configuration tasks are based on constraint satisfaction problem (CSP) solving. Most of them extend the traditional CSP approach in order to comply to the specific expressivity and dynamism requirements for 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, allowing for approaches to configuration tasks where the knowledge is distributed over a set of agents. Notably, the notions of constraint and nogood are generalized to an additional level of abstraction, extending inferences to types of variables. The usage of the new framework is exemplified by describing modifications to some complete algorithms for DisCSP when targeting DisGC.