Search

Globally operating enterprises selling large and complex products and services often have to deal with situations where variability models are locally developed to take into account the requirements of local markets. For example, cars sold on the U.S. market are represented by variability models in some or many aspects different from European ones. In order to support global variability management processes, variability models and the underlying knowledge bases often need to be integrated. This is a challenging task since an integrated knowledge base should not produce results which are different from those produced by the individual knowledge bases. In this paper, we introduce an approach to variability model integration that is based on the concepts of contextual modeling and conflict detection. We present the underlying concepts and the results of a corresponding performance analysis., M. Uta, A. Felfernig, G. Schenner, and J. Spoecklberger. Consistency-based Merging of Variability Models, Workshop on Configuration, pp. 9-12, Graz, Austria, 2018

Configuration is a successful application area of Artificial Intelligence. In the majority of the cases, configuration systems focus on configuring one solution (configuration) that satisfies the preferences of a single user or a group of users. In this paper, we introduce a new configuration approach - multi-configuration - that focuses on scenarios where the outcome of a configuration process is a set of configurations. Example applications thereof are the configuration of personalized exams for individual students, the configuration of project teams, reviewer-to-paper assignment, and hotel room assignments including individualized city trips for tourist groups. For multi-configuration scenarios, we exemplify a constraint satisfaction problem representation in the context of configuring exams. The paper is concluded with a discussion of open issues for future work., Comment: Cite as: A. Felfernig, A. Popescu, M. Uta, V.M. Le, S.P. Erdeniz, M. Stettinger, M. Atas, and T.N.T. Tran. Configuring Multiple Instances with Multi-Configuration. 23rd International Configuration Workshop, Vienna, Austria, CEUR, vol. 2945, pp. 45-47, 2021