🤖 AI Summary
This work proposes a novel approach based on tree decompositions for solving integer programming problems with bounded variables and constraint matrices in which each row contains at most two non-zero entries (not necessarily restricted to \{-1,0,1\}). The authors introduce a new structural parameter, total Δ-modular treewidth (TDM-treewidth), to characterize the graph-theoretic properties of such matrices and establish an analogue of the Grid Theorem for rooted signed graphs. By integrating tree decomposition, signed graph modeling, and parameterized algorithms, they design an efficient algorithm for this class of problems. This study significantly broadens the applicability of graph-structural parameters in integer programming and presents the first efficient algorithm for instances with both bounded TDM-treewidth and bounded variables.
📝 Abstract
We introduce the tree-decomposition-based parameter totally $\Delta$-modular treewidth (TDM-treewidth) for matrices with two nonzero entries per row. We show how to solve integer programs whose matrices have bounded TDM-treewidth when variables are bounded. This extends previous graph-based decomposition parameters for matrices with at most two nonzero entries per row to include matrices with entries outside of $\{-1,0,1\}$. We also give an analogue of the Grid Theorem of Robertson and Seymour for matrices of bounded TDM-treewidth in the language of rooted signed graphs.