In computer science and operations research, approximation algorithms are efficient algorithms that find approximate solutions to optimization problems...

specific parameter. These algorithms are designed to combine the best aspects of both traditional approximation algorithms and fixed-parameter tractability...

A minimax approximation algorithm (or L∞ approximation or uniform approximation) is a method to find an approximation of a mathematical function that...

also been work on approximation algorithms that do not use such sparsity assumptions. Feige (2004) describes a polynomial time algorithm that finds a clique...

Approximation Algorithms and Metaheuristics, Chapman & Hall/CRC. Goemans, Michel X.; Williamson, David P. (1995), "Improved approximation algorithms for...

of subset-sum. Therefore, it can be solved by algorithms developed for each of these problems. Algorithms developed for multiway number partitioning include:...

taking minors. In bounded degree graphs, effective approximation algorithms are known with approximation ratios that are constant for a fixed value of the...

the problem has instead concentrated on approximation algorithms for the problem. The goal of such algorithms is to find an approximate solution in polynomial...

a big gap between this inapproximability result and the known approximation algorithms for this problem. In the case of unweighted but directed graphs...

computer science (particularly algorithmics), a polynomial-time approximation scheme (PTAS) is a type of approximation algorithm for optimization problems...

collection of algorithms that can still be approximated to any specified degree. This means that the problem has a polynomial time approximation scheme. To...

answered with a simple 'yes' or 'no'. The field of approximation algorithms deals with algorithms to find near-optimal solutions to hard problems. The...

describes approximation of law as "a unique obligation of membership in the European Union". Approximation algorithm – Class of algorithms that find approximate...

only estimated via noisy observations. In a nutshell, stochastic approximation algorithms deal with a function of the form f ( θ ) = E ξ ⁡ [ F ( θ , ξ )...

practice. These algorithms are called auction algorithms, push-relabel algorithms, or preflow-push algorithms. Some of these algorithms were shown to be...

matter of fact, the term "algorithm" was not commonly extended to approximation algorithms until later; the Christofides algorithm was initially referred...

branch-and-bound algorithm. There are a few variations to the greedy algorithm: Pure greedy algorithms Orthogonal greedy algorithms Relaxed greedy algorithms Greedy...

communication Chuzhoy, Julia; Ostrovsky, Rafail; Rabani, Yuval (2006). "Approximation Algorithms for the Job Interval Selection Problem and Related Scheduling Problems"...

polynomial-time approximation algorithms with approximation ratio bounded by a constant (or constant-factor approximation algorithms for short). In simple...

produced with sophisticated algorithms. In addition, many approximation algorithms exist. For example, the first fit algorithm provides a fast but often...

programming algorithms that can solve it exactly. As both n and L grow large, SSP is NP-hard. The complexity of the best known algorithms is exponential...

cannot in general be solved exactly, and one must often resort to approximation algorithms and heuristics There are several solvers submitted to the last...

matching), for example, the Hopcroft–Karp algorithm. There is a very simple polynomial-time 3-approximation algorithm for 3-dimensional matching: find any...

(they are symmetric and obey the triangle inequality). It is an approximation algorithm that guarantees that its solutions will be within a factor of 3/2...

efficient algorithm that can compute γ(G) for all graphs G. However, there are efficient approximation algorithms, as well as efficient exact algorithms for...

often implemented as an A* search algorithm. In addition to exact algorithms, a number of efficient approximation algorithms are also known. Most of them have...

existence of an approximation preserving L-reduction from the vertex cover problem to it; Existing constant-factor approximation algorithms. The best known...

perform a computation. Algorithms are used as specifications for performing calculations and data processing. More advanced algorithms can use conditionals...

NP-hard. This result prompted research on approximation algorithms with the aim of developing a tractable approximation to probabilistic inference. In 1993...

such an algorithm will find the nearest neighbor in a majority of cases, but this depends strongly on the dataset being queried. Algorithms that support...