A Fixed-Parameter Algorithm for Random Instances of Weighted d-CNF Satisfiability
Yong Gao

TL;DR
This paper demonstrates that random instances of the weighted d-CNF satisfiability problem are fixed-parameter tractable with high probability, providing a comprehensive understanding of their typical-case computational complexity.
Contribution
The authors establish fixed-parameter tractability for random weighted d-CNF SAT instances and extend results to various random models, advancing the understanding of typical-case complexity.
Findings
Random instances are solvable in polynomial time with high probability.
Results hold for models with restricted clause structures.
Provides a near-complete characterization of typical-case behavior.
Abstract
We study random instances of the weighted -CNF satisfiability problem (WEIGHTED -SAT), a generic W[1]-complete problem. A random instance of the problem consists of a fixed parameter and a random -CNF formula generated as follows: for each subset of variables and with probability , a clause over the variables is selected uniformly at random from among the clauses that contain at least one negated literals. We show that random instances of WEIGHTED -SAT can be solved in -time with high probability, indicating that typical instances of WEIGHTED -SAT under this instance distribution are fixed-parameter tractable. The result also hold for random instances from the model where clauses containing less than negated literals are forbidden, and for random instances of…
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Taxonomy
TopicsAdvanced Graph Theory Research · Constraint Satisfaction and Optimization · Complexity and Algorithms in Graphs
