SettingsApproximation algorithms
Alpha max plus beta min algorithm
The alpha max plus beta min algorithm is a high-speed approximation of the square root of the sum of two squares.
The alpha max plus beta min algorithm is a high-speed approximation of the square root of the sum of two squares.
Approximation algorithm
In computer science and operations research, approximation algorithms are algorithms used to find approximate solutions to optimization problems.
In computer science and operations research, approximation algorithms are algorithms used to find approximate solutions to optimization problems.
APX
In complexity theory the class APX (an abbreviation of "approximable") is the set of NPO optimization problems that allow polynomial-time approximation algorithms with approximation ratio bounde...
In complexity theory the class APX (an abbreviation of "approximable") is the set of NPO optimization problems that allow polynomial-time approximation algorithms with approximation ratio bounde...
Christofides algorithm
The goal of the Christofides heuristic algorithm is to find a solution to the instances of the traveling salesman problem where the edge weights satisfy the triangle inequality.
The goal of the Christofides heuristic algorithm is to find a solution to the instances of the traveling salesman problem where the edge weights satisfy the triangle inequality.
Domination analysis
Domination analysis of an approximation algorithm is a way to estimate its performance, introduced by Glover and Punnen in 1997.
Domination analysis of an approximation algorithm is a way to estimate its performance, introduced by Glover and Punnen in 1997.
K-approximation of k-hitting set
In computer science, k-approximation of k-hitting set is an approximation algorithm for weighted hitting set.
In computer science, k-approximation of k-hitting set is an approximation algorithm for weighted hitting set.
Karloff–Zwick algorithm
The Karloff–Zwick algorithm, in computational complexity theory, is a randomised approximation algorithm taking an instance of MAX-3SAT Boolean satisfiability problem as input.
The Karloff–Zwick algorithm, in computational complexity theory, is a randomised approximation algorithm taking an instance of MAX-3SAT Boolean satisfiability problem as input.
L-reduction
L-reduction ("linear reduction") is a transformation of optimization problems which linearly preserves approximability features.
L-reduction ("linear reduction") is a transformation of optimization problems which linearly preserves approximability features.
Metric k-center
In graph theory, the metric k-center, is a combinatorial optimization problem studied in theoretical computer science.
In graph theory, the metric k-center, is a combinatorial optimization problem studied in theoretical computer science.
Minimum k-cut
In mathematics, the minimum k-cut, is a combinatorial optimization problem that requires finding a set of edges whose removal would partition the graph to k connected components.
In mathematics, the minimum k-cut, is a combinatorial optimization problem that requires finding a set of edges whose removal would partition the graph to k connected components.
Nearest neighbor search
Nearest neighbor search (NNS), also known as proximity search, similarity search or closest point search, is an optimization problem for finding closest points in metric ...
Nearest neighbor search (NNS), also known as proximity search, similarity search or closest point search, is an optimization problem for finding closest points in metric ...
Nearest neighbour algorithm
The nearest neighbour algorithm was one of the first algorithms used to determine a solution to the travelling salesman problem.
The nearest neighbour algorithm was one of the first algorithms used to determine a solution to the travelling salesman problem.
Polynomial-time approximation scheme
In computer science, a polynomial-time approximation scheme is a type of approximation algorithm for optimization problems.
In computer science, a polynomial-time approximation scheme is a type of approximation algorithm for optimization problems.
Property testing
In computer science, a property testing algorithm for a decision problem is an algorithm whose query complexity to its input is much smaller than the instance size of the problem.
In computer science, a property testing algorithm for a decision problem is an algorithm whose query complexity to its input is much smaller than the instance size of the problem.
Submodular set function
In mathematics, submodular functions are set functions which usually appear in approximation algorithms, functions modeling user preferences in game theory.
In mathematics, submodular functions are set functions which usually appear in approximation algorithms, functions modeling user preferences in game theory.
Symmetry testing
Symmetry testing is the special case of property testing for testing if a Boolean function is a symmetric function.
Symmetry testing is the special case of property testing for testing if a Boolean function is a symmetric function.
Ε-approximate nearest neighbor search
ε-approximate nearest neighbor search is a special case of nearest neighbor search in which we are searching for points that are close to a query point.
ε-approximate nearest neighbor search is a special case of nearest neighbor search in which we are searching for points that are close to a query point.