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

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

Philip Wolfe in 1956. In each iteration, the Frank–Wolfe algorithm considers a linear approximation of the objective function, and moves towards a minimizer...

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

An approximation is anything that is intentionally similar but not exactly equal to something else. The word approximation is derived from Latin approximatus...

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

A parameterized approximation algorithm is a type of algorithm that aims to find approximate solutions to NP-hard optimization problems in polynomial time...

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

maximum. Although the approximation ratio of this algorithm is weak, it is the best known to date. The results on hardness of approximation described below...

time algorithm using dynamic programming. There is a fully polynomial-time approximation scheme, which uses the pseudo-polynomial time algorithm as a...

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

(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...

approximation algorithm achieves an approximation ratio strictly less than one. There is a simple randomized 0.5-approximation algorithm: for each vertex...

trivial algorithm attains a (d − 1)-approximation algorithm for the maximum independent set. In fact, it is possible to get much better approximation ratios:...

optimization, greedy algorithms optimally solve combinatorial problems having the properties of matroids and give constant-factor approximations to optimization...

quasi-Newton methods like BFGS, is an algorithm of an iterative method or a method of successive approximation. An iterative method is called convergent...

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 )...

is an approximation algorithm for performing an N-body simulation. It is notable for having order O(n log n) compared to a direct-sum algorithm which...

preserve the quality of approximations to that solution. If the graph is a metric space then there is an efficient approximation algorithm that finds a Hamiltonian...

the runtime is O(n) and the approximation ratio is at most 3/2 ("approximation ratio" means the larger sum in the algorithm output, divided by the larger...

understanding its approximation hardness". The best polynomial time approximation algorithm known for this case achieves only a very weak approximation ratio, n...

The nearest neighbour algorithm was one of the first algorithms used to solve the travelling salesman problem approximately. In that problem, the salesman...

any algorithm for the knapsack problem into an approximation algorithm for the GAP. Using any α {\displaystyle \alpha } -approximation algorithm ALG 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...

know quasi-polynomial time algorithms, but no polynomial time algorithm is known. Such problems arise in approximation algorithms; a famous example is the...

where r is a number in (0,1) called the approximation ratio. The following very simple algorithm has an approximation ratio of 1/2: Order the inputs by descending...

character recognition Statistical classification – see k-nearest neighbor algorithm Computer vision – for point cloud registration Computational geometry...

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

indeed gives a factor- log ⁡ n {\displaystyle \scriptstyle \log n} approximation algorithm for the minimum set cover problem. See randomized rounding#setcover...

This is a list of algorithm general topics. Analysis of algorithms Ant colony algorithm Approximation algorithm Best and worst cases Big O notation Combinatorial...