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• W49964765 abstract "Decomposition is an effective technique for solving discrete Constraint Optimization Problems (COPs) with low tree-width. On problems with high tree-width, however, existing decomposition algorithms offer little advantage over branch and bound search (B&B). In this paper we propose a method for exploiting decomposition on problems with high treewidth. Our technique involves modifying B&B to detect and exploit decomposition on a selected subset of the problem's objectives. Decompositions over this subset, generated during search, are exploited to compute tighter bounds allowing B&B to prune more of its search space. We present a heuristic for selecting an appropriate subset of objectives--one that readily decomposes during search and yet can still provide good bounds. We demonstrate empirically that our approach can significantly improve B&B's performance and outperform standard decomposition algorithms on a variety of high tree-width problems." @default.
• W49964765 created "2016-06-24" @default.
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• W49964765 date "2009-07-11" @default.
• W49964765 modified "2023-09-24" @default.
• W49964765 title "Exploiting decomposition on constraint problems with high tree-width" @default.
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