Abstract
We focus on the recently introduced problem of maximizing the number of satisfied constraints in a qualitative constraint network (QCN), called the MAX-QCN problem. We present a particular local search method for solving the MAX-QCN problem of a given QCN, which involves first obtaining a partial scenario S of that QCN and then exploring neighboring scenarios that are obtained by disconnecting a variable of S and repositioning it appropriately. The experimentation that we have conducted shows the interest of our approach for maximizing satisfiability in qualitative spatial and temporal constraint networks.
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CITATION STYLE
Condotta, J. F., Mensi, A., Nouaouri, I., Sioutis, M., & Saïd, L. B. (2016). Local search for maximizing satisfiability in qualitative spatial and temporal constraint networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9883 LNAI, pp. 247–258). Springer Verlag. https://doi.org/10.1007/978-3-319-44748-3_24
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