arXiv AI

Solving Minimum Span Antibandwidth and Cyclic Antibandwidth Labeling Problems

The paper introduces the Minimum Span Antibandwidth and Cyclic Antibandwidth Labeling (MSABL/MSCABL) problems, which fix a minimum (cyclic) distance between adjacent vertex labels and aim to minimize the overall label span. A unified Boolean Satisfiability (SAT) framework is developed, formulating the problems as a sequence of decision problems and exploiting monotonicity to accelerate search. Two SAT solving strategies—parallel and incremental—are evaluated on benchmark instances from the Harwell‑Boeing Sparse Matrix Collection and compared with commercial solvers, showing that SAT-based approaches are highly competitive, with the parallel method best for MSCABL and the incremental method best for MSABL.

Hugging Face Trending Papers
Sep 17

Solving Minimum Span Antibandwidth and Cyclic Antibandwidth Labeling Problems

The paper introduces the Minimum Span Antibandwidth and Cyclic Antibandwidth Labeling (MSABL/MSCABL) problems, which fix a minimum (cyclic) distance between labels of adjacent vertices and aim to minimize the overall label span. A unified Boolean Satisfiability (SAT) framework is developed, formulating the problems as a sequence of decision problems and exploiting monotonicity to accelerate search. Two SAT solving strategies—parallel and incremental—are evaluated on benchmark instances, showing that SAT-based approaches are highly competitive with commercial solvers, especially for MSCABL.

arXiv AI
Jun 8

A Study of Parallel Continuous Local Search

arXiv:2606. 06656v1 Announce Type: new Abstract: We study parallel Continuous Local Search (CLS) as a solution approach for Boolean satisfiability problems with symmetric pseudo-Boolean (PB) constraints.

By Cody J Christopher, Charles Gretton
arXiv Machine Learning
Jun 8

The Proxy Benders Decomposition

arXiv:2606. 07403v1 Announce Type: cross Abstract: Benders decomposition is a fundamental framework for solving large-scale mixed-integer optimization problems with complicating variables that, when fixed, yield significantly easier subproblems.

By Changkun Guan, El Mehdi Er Raqabi, Mathieu Tanneau, Pascal Van Hentenryck