Time Complexity of Constraint Satisfaction via Universal Algebra
Peter Jonsson, Victor Lagerkvist, Biman Roy

TL;DR
This paper investigates the exponential-time complexity of NP-complete constraint satisfaction problems (CSPs), establishing lower bounds under the ETH and exploring how algebraic properties influence computational difficulty.
Contribution
It proves that finite-domain NP-complete CSPs lack subexponential algorithms under ETH and introduces a relation that bounds the complexity of certain CSP subclasses.
Findings
Finite-domain NP-complete CSPs are not solvable in subexponential time under ETH.
A specific relation (SD) provides a lower bound on the complexity of certain CSP subclasses.
The complexity of CSP({SD}) decreases as the domain size increases, unless ETH is false.
Abstract
The exponential-time hypothesis (ETH) states that 3-SAT is not solvable in subexponential time, i.e. not solvable in O(c^n) time for arbitrary c > 1, where n denotes the number of variables. Problems like k-SAT can be viewed as special cases of the constraint satisfaction problem (CSP), which is the problem of determining whether a set of constraints is satisfiable. In this paper we study thef worst-case time complexity of NP-complete CSPs. Our main interest is in the CSP problem parameterized by a constraint language Gamma (CSP(Gamma)), and how the choice of Gamma affects the time complexity. It is believed that CSP(Gamma) is either tractable or NP-complete, and the algebraic CSP dichotomy conjecture gives a sharp delineation of these two classes based on algebraic properties of constraint languages. Under this conjecture and the ETH, we first rule out the existence of subexponential…
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Taxonomy
TopicsConstraint Satisfaction and Optimization · Advanced Graph Theory Research · Formal Methods in Verification
