Fixed-Parameter and Approximation Algorithms: A New Look

Abstract: A Fixed-Parameter Tractable (\FPT) $\rho$-approximation algorithm for a minimization (resp. maximization) parameterized problem $P$ is an FPT algorithm that, given an instance $(x, k)\in P$ computes a solution of cost at most $k \cdot \rho(k)$ (resp. $k/\rho(k)$) if a solution of cost at most (resp. at least) $k$ exists; otherwise the output can be arbitrary. For well-known intractable problems such as the W[1]-hard {Clique} and W[2]-hard {Set Cover} problems, the natural question is whether we can get any \FPT-approximation. It is widely believed that both {Clique} and {Set-Cover} admit no FPT $\rho$-approximation algorithm, for any increasing function $\rho$. Assuming standard conjectures such as the Exponential Time Hypothesis (ETH) \cite{eth-paturi} and the Projection Games Conjecture (PGC) \cite{r3}, we make the first progress towards proving this conjecture by showing that 1. Under the ETH and PGC, there exist constants $F_1, F_2 &gt;0$ such that the {Set Cover} problem does not admit an FPT approximation algorithm with ratio $k<sup>{F_1}$ in $$2^{{k^{F_2}}\cdot} \text{poly}(N,M)$$ time, where $N$ is the size of the universe and $M$ is the number of sets. 2. Unless $\NP\subseteq \SUBEXP$, for every $1&gt; \delta &gt; 0$ there exists a constant $F(\delta)&gt;0$ such that {Clique} has no FPT cost approximation with ratio $k<sup>{1-\delta}$ in $2^{{k^{F}}\cdot} \text{poly}(n)$ time, where $n$ is the number of vertices in the graph. In the second part of the paper we consider various W[1]-hard problems such as {\dst}, {\dsf}, Directed Steiner Network and {\mec}. For all these problem we give polynomial time $f(\text{OPT})$-approximation algorithms for some small function $f$ (the largest approximation ratio we give is $\text{OPT}<sup>2$).