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Solving Minimum Span Antibandwidth and Cyclic Antibandwidth Labeling Problems

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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.

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arXiv AI
Sep 18

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.

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