Constraint Satisfaction Problems Parameterized Above or Below Tight Bounds: A Survey
G. Gutin, A. Yeo

TL;DR
This survey reviews recent advances in parameterized algorithms and kernelization for constraint satisfaction problems above or below tight bounds, highlighting new results and open questions in the field.
Contribution
It provides a comprehensive overview of polynomial kernels and algorithms for problems like MaxSat and MaxLin2 parameterized above bounds, including recent developments and open challenges.
Findings
Several polynomial kernels have been developed for these problems.
Recent parameterized algorithms improve solving efficiency.
Open questions remain in kernelization for certain problem variants.
Abstract
We consider constraint satisfaction problems parameterized above or below tight bounds. One example is MaxSat parameterized above : given a CNF formula with clauses, decide whether there is a truth assignment that satisfies at least clauses, where is the parameter. Among other problems we deal with are MaxLin2-AA (given a system of linear equations over in which each equation has a positive integral weight, decide whether there is an assignment to the variables that satisfies equations of total weight at least , where is the total weight of all equations), Max--Lin2-AA (the same as MaxLin2-AA, but each equation has at most variables, where is a constant) and Max--Sat-AA (given a CNF formula with clauses in which each clause has at most literals, decide whether there is a truth assignment satisfying at least…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Graph Theory Research · Complexity and Algorithms in Graphs · Constraint Satisfaction and Optimization
