A fully polynomial-time approximation scheme (FPTAS) is an algorithm for finding approximate solutions to function problems, especially optimization problems. An FPTAS takes as input an instance of the problem and a parameter ε > 0. It returns as output a value which is at least times the correct value, and at most times the correct value.
In the context of optimization problems, the correct value is understood to be the value of the optimal solution, and it is often implied that an FPTAS should produce a valid solution (and not just the value of the solution). Returning a value and finding a solution with that value are equivalent assuming that the problem possesses self reducibility.
Importantly, the run-time of an FPTAS is polynomial in the problem size and in 1/ε. This is in contrast to a general polynomial-time approximation scheme (PTAS). The run-time of a general PTAS is polynomial in the problem size for each specific ε, but might be exponential in 1/ε.[1]
The term FPTAS may also be used to refer to the class of problems that have an FPTAS. FPTAS is a subset of PTAS, and unless P = NP, it is a strict subset.[2]
- ^ G. Ausiello, P. Crescenzi, G. Gambosi, V. Kann, A. Marchetti-Spaccamela, and M. Protasi. Complexity and Approximation: Combinatorial optimization problems and their approximability properties, Springer-Verlag, 1999.
- ^ Jansen, Thomas (1998), "Introduction to the Theory of Complexity and Approximation Algorithms", in Mayr, Ernst W.; Prömel, Hans Jürgen; Steger, Angelika (eds.), Lectures on Proof Verification and Approximation Algorithms, Lecture Notes in Computer Science, vol. 1367, Springer, pp. 5–28, doi:10.1007/BFb0053011, ISBN 9783540642015. See discussion following Definition 1.30 on p. 20.