Jul 23, 2025 · The goal of the approximation algorithm is to come as close as possible to the optimal solution in polynomial time. Such algorithms are called approximation algorithms or …

In computer science and operations research, approximation algorithms are efficient algorithms that find approximate solutions to optimization problems (in particular NP-hard problems) with …

Approximation algorithms: procedures which are proven to give solutions within a factor of optimum. Of these approaches, approximation algorithms are arguably the most …

Linear programming is an extremely versatile technique for designing approximation algorithms, because it is one of the most general and expressive problems that we know how to solve in …

In each of the 27 chapters an important combinatorial optimization problem is presented and one or more approximation algorithms for it are clearly and concisely described and analyzed.

Approximation algorithms are algorithms designed to solve problems that are not solvable in polynomial time for approximate solutions. These problems are known as NP complete problems.

A family of approximation algorithms {Ae : e > 0} for a problem P. Ae is a (1 + e) - approximation algorithm for P. Ae is runs in time polynomial in input size for a fixed e.

Given an optimization problem P, an algorithm A is said to be an approximation algorithm for P, if for any given instance I, it returns an approximate solution, that is a feasible solution.

A Fully Polynomial Time Approximation Scheme (FPTAS) is an approximation algorithm that runs in time polynomial in both n and c. For example, a O(n2/E) approximation algorithm is a PTAS …

Today’s lecture focuses on the first idea, to derive polynomial-time approximation algorithms.