Abstract
Local search algorithms have been very successful for solving constraint satisfaction problems (CSP). However, a major weakness has been that local search is unable to detect unsolvability and is thus not suitable for highly constrained or overconstrained problems. In this paper, we present a scheme where a local search algorithm, the breakout algorithm, is used to identify hard or unsolvable subproblems and to derive a variable ordering that places the hardest subproblems first.
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Eisenberg, C., Faltings, B. (2003). Using the Breakout Algorithm to Identify Hard and Unsolvable Subproblems. In: Rossi, F. (eds) Principles and Practice of Constraint Programming – CP 2003. CP 2003. Lecture Notes in Computer Science, vol 2833. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45193-8_60
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DOI: https://doi.org/10.1007/978-3-540-45193-8_60
Publisher Name: Springer, Berlin, Heidelberg
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