MarketList of algorithms
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List of algorithms

An algorithm is a fundamental set of rules or defined procedures that are typically designed and used to be a simpler way to solve a specific problem or a broad set of problems.

Combinatorial algorithms
General combinatorial algorithmsBrent's algorithm: finds a cycle in function value iterations using only two iterators • Floyd's cycle-finding algorithm: finds a cycle in function value iterations • Gale–Shapley algorithm: solves the stable matching problemPseudorandom number generators (uniformly distributed—see also List of pseudorandom number generators for other PRNGs with varying degrees of convergence and varying statistical quality): • ACORN generatorBlum Blum ShubLagged Fibonacci generatorLinear congruential generatorMersenne Twister Graph algorithmsBlossom algorithm: algorithm for constructing maximum-cardinality matching on graphs. • Coloring algorithm: algorithms for graph (vertex or edge) coloring (subject to constraints, e.g. proper coloring or list coloring) • Hopcroft–Karp algorithm: convert a bipartite graph to a maximum-cardinality matchingHungarian algorithm: algorithm for finding a perfect matchingPrüfer coding: conversion between a labeled tree and its Prüfer sequenceTarjan's off-line lowest common ancestors algorithm: computes lowest common ancestors for pairs of nodes in a tree • Topological sort: finds linear order of nodes (e.g. jobs) based on their dependencies. Graph drawingCoin graph drawing algorithms for finite connected planar graphs (approximately computing the theoretical circle-packing given by the Koebe-Andreev-Thurston theorem). See also Fáry's theorem on straight-line drawings of planar graphs. • Force-based algorithms (also known as force-directed algorithms or spring-based algorithms) • Spectral layout Network theory • Network analysis • Link analysis • Girvan–Newman algorithm: detect communities in complex systems • Web link analysis • Hyperlink-Induced Topic Search (HITS) (also known as Hubs and authorities) • PageRankTrustRankFlow networks • Dinic's algorithm: is a strongly polynomial algorithm for computing the maximum flow in a flow network. • Edmonds–Karp algorithm: implementation of Ford–Fulkerson • Ford–Fulkerson algorithm: computes the maximum flow in a graph • Karger's algorithm: a Monte Carlo method to compute the minimum cut of a connected graph • Push–relabel algorithm: computes a maximum flow in a graph Routing for graphsEdmonds' algorithm (also known as Chu–Liu/Edmonds' algorithm): find maximum or minimum branchings • Euclidean minimum spanning tree: algorithms for computing the minimum spanning tree of a set of points in the plane • Longest path problem: find a simple path of maximum length in a given graph • Minimum spanning treeBorůvka's algorithmKruskal's algorithmPrim's algorithmReverse-delete algorithmNonblocking minimal spanning switch say, for a telephone exchangeShortest path problemBellman–Ford algorithm: computes shortest paths in a weighted graph (where some of the edge weights may be negative) • Dijkstra's algorithm: computes shortest paths in a graph with non-negative edge weights • Floyd–Warshall algorithm: solves the all pairs shortest path problem in a weighted, directed graph • Johnson's algorithm: all pairs shortest path algorithm in sparse weighted directed graph • Transitive closure problem: find the transitive closure of a given binary relation • Traveling salesman problemChristofides algorithmNearest neighbour algorithmVehicle routing problem • Clarke and Wright Saving algorithm • Warnsdorff's rule: a heuristic method for solving the Knight's tour problem Graph searchA*: special case of best-first search that uses heuristics to improve speed • B*: a best-first graph search algorithm that finds the least-cost path from a given initial node to any goal node (out of one or more possible goals) • Backtracking: abandons partial solutions when they are found not to satisfy a complete solution • Beam search: is a heuristic search algorithm that is an optimization of best-first search that reduces its memory requirement • Beam stack search: integrates backtracking with beam searchBest-first search: traverses a graph in the order of likely importance using a priority queueBidirectional search: find the shortest path from an initial vertex to a goal vertex in a directed graph • Breadth-first search: traverses a graph level by level • Brute-force search: an exhaustive and reliable search method, but computationally inefficient in many applications • D*: an incremental heuristic search algorithm • Depth-first search: traverses a graph branch by branch • Dijkstra's algorithm: a special case of A* for which no heuristic function is used • General Problem Solver: a seminal theorem-proving algorithm intended to work as a universal problem solver machine. • Iterative deepening depth-first search (IDDFS): a state space search strategy • Jump point search: an optimization to A* which may reduce computation time by an order of magnitude using further heuristics • Lexicographic breadth-first search (also known as Lex-BFS): a linear time algorithm for ordering the vertices of a graph • SSS*: state space search traversing a game tree in a best-first fashion similar to that of the A* search algorithm • Uniform-cost search: a tree search that finds the lowest-cost route where costs vary SubgraphsCliquesBron–Kerbosch algorithm: a technique for finding maximal cliques in an undirected graph • MaxCliqueDyn maximum clique algorithm: find a maximum clique in an undirected graph • Strongly connected componentsKosaraju's algorithmPath-based strong component algorithmTarjan's strongly connected components algorithmSubgraph isomorphism problem Sequence algorithms Approximate sequence matchingBitap algorithm: fuzzy algorithm that determines if strings are approximately equal. • Phonetic algorithms • Daitch–Mokotoff Soundex: a Soundex refinement which allows matching of Slavic and Germanic surnames • Double Metaphone: an improvement on Metaphone • Match rating approach: a phonetic algorithm developed by Western Airlines • Metaphone: an algorithm for indexing words by their sound, when pronounced in English • NYSIIS: phonetic algorithm, improves on SoundexSoundex: a phonetic algorithm for indexing names by sound, as pronounced in English • String metrics: computes a similarity or dissimilarity (distance) score between two pairs of text strings • Damerau–Levenshtein distance: computes a distance measure between two strings, improves on Levenshtein distanceDice's coefficient (also known as the Dice coefficient): a similarity measure related to the Jaccard indexHamming distance: sum number of positions which are different • Jaro–Winkler distance: is a measure of similarity between two strings • Levenshtein edit distance: computes a metric for the amount of difference between two sequences • Trigram search: search for text when the exact syntax or spelling of the target object is not precisely known Selection algorithmsIntroselectQuickselect Sequence searchLinear search: locates an item in an unsorted sequence • Selection algorithm: finds the kth largest item in a sequence • Sorted lists • Binary search algorithm: locates an item in a sorted sequence • Eytzinger binary search: cache friendly binary search algorithm • Fibonacci search technique: search a sorted sequence using a divide and conquer algorithm that narrows down possible locations with the aid of Fibonacci numbersJump search (or block search): linear search on a smaller subset of the sequence • Predictive search: binary-like search which factors in magnitude of search term versus the high and low values in the search. Sometimes called dictionary search or interpolated search. • Uniform binary search: an optimization of the classic binary search algorithm • Ternary search: a technique for finding the minimum or maximum of a function that is either strictly increasing and then strictly decreasing or vice versa Sequence mergingk-way merge algorithm • Simple merge algorithm • Union (merge, with elements on the output not repeated) Sequence permutationsFisher–Yates shuffle (also known as the Knuth shuffle): randomly shuffle a finite set • Heap's permutation generation algorithm: interchange elements to generate next permutation • Schensted algorithm: constructs a pair of Young tableaux from a permutation • Steinhaus–Johnson–Trotter algorithm (also known as the Johnson–Trotter algorithm): generates permutations by transposing elements Sequence combinations Sequence alignmentDynamic time warping: measure similarity between two sequences which may vary in time or speed • Hirschberg's algorithm: finds the least cost sequence alignment between two sequences, as measured by their Levenshtein distanceNeedleman–Wunsch algorithm: find global alignment between two sequences • Smith–Waterman algorithm: find local sequence alignment Sequence sorting • Exchange sorts • Bubble sort: for each pair of indices, swap the items if out of order • Cocktail shaker sort or bidirectional bubble sort, a bubble sort traversing the list alternately from front to back and back to front • Comb sortGnome sortOdd–even sortQuicksort: divide list into two, with all items on the first list coming before all items on the second list.; then sort the two lists. Often the method of choice • Humorous or ineffective • Bogosort: the list is randomly shuffled until it happens to be sorted • SlowsortStooge sort • Hybrid • FlashsortIntrosort: begin with quicksort and switch to heapsort when the recursion depth exceeds a certain level • Timsort: adaptative algorithm derived from merge sort and insertion sort. Used in Python 2.3 and up, and Java SE 7. • Insertion sorts • Cycle sort: in-place with theoretically optimal number of writes • Insertion sort: determine where the current item belongs in the list of sorted ones, and insert it there • Library sortPatience sortingShell sort: an attempt to improve insertion sort • Tree sort (binary tree sort): build binary tree, then traverse it to create sorted list • Merge sorts • Merge sort: sort the first and second half of the list separately, then merge the sorted lists • SlowsortStrand sort • Non-comparison sorts • Bead sortBucket sortBurstsort: build a compact, cache efficient burst trie and then traverse it to create sorted output • Counting sortPigeonhole sortPostman sort: variant of Bucket sort which takes advantage of hierarchical structure • Radix sort: sorts strings letter by letter • Selection sorts • Heapsort: convert the list into a heap, keep removing the largest element from the heap and adding it to the end of the list • Selection sort: pick the smallest of the remaining elements, add it to the end of the sorted list • Smoothsort • Other • Bitonic sorterPancake sortingSpaghetti sortTopological sort • Unknown class • Samplesort SubsequencesLongest common subsequence problem: Find the longest subsequence common to all sequences in a set of sequences • Longest increasing subsequence problem: Find the longest increasing subsequence of a given sequence • Ruzzo–Tompa algorithm: Find all non-overlapping, contiguous, maximal scoring subsequences in a sequence of real numbers • Shortest common supersequence problem: Find the shortest supersequence that contains two or more sequences as subsequences SubstringsKadane's algorithm: finds the contiguous subarray with largest sum in an array of numbers • Longest common substring problem: find the longest string (or strings) that is a substring (or are substrings) of two or more strings • Matching wildcardsKrauss matching wildcards algorithm: an open-source non-recursive algorithm • Rich Salz' wildmat: a widely used open-source recursive algorithm • Substring searchAho–Corasick string matching algorithm: trie based algorithm for finding all substring matches to any of a finite set of strings • Boyer–Moore–Horspool algorithm: Simplification of Boyer–Moore • Boyer–Moore string-search algorithm: amortized linear (sublinear in most times) algorithm for substring search • Knuth–Morris–Pratt algorithm: substring search which bypasses reexamination of matched characters • Rabin–Karp string search algorithm: searches multiple patterns efficiently • Zhu–Takaoka string matching algorithm: a variant of Boyer–Moore • Ukkonen's algorithm: a linear-time, online algorithm for constructing suffix trees ==Computational mathematics==
Computational mathematics
Abstract algebraChien search: a recursive algorithm for determining roots of polynomials defined over a finite field • Schreier–Sims algorithm: computing a base and strong generating set (BSGS) of a permutation groupTodd–Coxeter algorithm: Procedure for generating cosets. Computer algebraBuchberger's algorithm: finds a Gröbner basisCantor–Zassenhaus algorithm: factor polynomials over finite fields • Faugère F4 algorithm: finds a Gröbner basis (also mentions the F5 algorithm) • Gosper's algorithm: find sums of hypergeometric terms that are themselves hypergeometric terms • Knuth–Bendix completion algorithm: for rewriting rule systems • Multivariate division algorithm: for polynomials in several indeterminates • Pollard's kangaroo algorithm (also known as Pollard's lambda algorithm): an algorithm for solving the discrete logarithm problem • Polynomial long division: an algorithm for dividing a polynomial by another polynomial of the same or lower degree • Risch algorithm: an algorithm for the calculus operation of indefinite integration (i.e. finding antiderivatives) GeometryClosest pair problem: find the pair of points (from a set of points) with the smallest distance between them • Collision detection algorithms: check for the collision or intersection of two given solids • Cone algorithm: identify surface points • Convex hull algorithms: determining the convex hull of a set of points • Chan's algorithmGift wrapping algorithm or Jarvis march • Graham scanKirkpatrick–Seidel algorithmQuickhullEuclidean distance transform: computes the distance between every point in a grid and a discrete collection of points. • Geometric hashing: a method for efficiently finding two-dimensional objects represented by discrete points that have undergone an affine transformationGilbert–Johnson–Keerthi distance algorithm: determining the smallest distance between two convex shapes. • Jump-and-Walk algorithm: an algorithm for point location in triangulations • Laplacian smoothing: an algorithm to smooth a polygonal mesh • Line segment intersection: finding whether lines intersect, usually with a sweep line algorithmBentley–Ottmann algorithmShamos–Hoey algorithmMinimum bounding box algorithms: find the oriented minimum bounding box enclosing a set of points • Nearest neighbor search: find the nearest point or points to a query point • Nesting algorithm: make the most efficient use of material or space • Point in polygon algorithms: tests whether a given point lies within a given polygon • Point set registration algorithms: finds the transformation between two point sets to optimally align them. • Rotating calipers: determine all antipodal pairs of points and vertices on a convex polygon or convex hull. • Shoelace algorithm: determine the area of a polygon whose vertices are described by ordered pairs in the plane • TriangulationDelaunay triangulationChew's second algorithm: create quality constrained Delaunay triangulations • Ruppert's algorithm (also known as Delaunay refinement): create quality Delaunay triangulations • Marching triangles: reconstruct two-dimensional surface geometry from an unstructured point cloudPolygon triangulation algorithms: decompose a polygon into a set of triangles • QuasitriangulationVoronoi diagrams, geometric dual of Delaunay triangulationBowyer–Watson algorithm: create voronoi diagram in any number of dimensions • Fortune's Algorithm: create voronoi diagram Number theoretic algorithmsBinary GCD algorithm: Efficient way of calculating GCD. • Booth's multiplication algorithmChakravala method: a cyclic algorithm to solve indeterminate quadratic equations, including Pell's equationDiscrete logarithm: • Baby-step giant-stepIndex calculus algorithmPohlig–Hellman algorithmPollard's rho algorithm for logarithmsEuclidean algorithm: computes the greatest common divisorExtended Euclidean algorithm: also solves the equation ax + by = cInteger factorization: breaking an integer into its prime factors • Congruence of squaresDixon's algorithmFermat's factorization methodGeneral number field sieveLenstra elliptic curve factorizationPollard's p − 1 algorithmPollard's rho algorithmprime factorization algorithmQuadratic sieveShor's algorithmSpecial number field sieveTrial divisionLenstra–Lenstra–Lovász algorithm (also known as LLL algorithm): find a short, nearly orthogonal lattice basis in polynomial time • Modular square root: computing square roots modulo a prime number • Berlekamp's root finding algorithmCipolla's algorithmTonelli–Shanks algorithmMultiplication algorithms: fast multiplication of two numbers • Karatsuba algorithmSchönhage–Strassen algorithmToom–Cook multiplicationOdlyzko–Schönhage algorithm: calculates nontrivial zeroes of the Riemann zeta functionPrimality tests: determining whether a given number is primeAKS primality testBaillie–PSW primality testFermat primality testLucas primality testMiller–Rabin primality testSieve of AtkinSieve of EratosthenesSieve of Sundaram Numerical algorithms Differential equation solvingBackward Euler methodEuler methodLinear multistep methods • Multigrid methods (MG methods), a group of algorithms for solving differential equations using a hierarchy of discretizations • Partial differential equation: • Crank–Nicolson method for diffusion equations • Finite difference methodLax–Wendroff for wave equations • Runge–Kutta methodsEuler integrationTrapezoidal rule (differential equations)Verlet integration (): integrate Newton's equations of motion Elementary and special functionsComputation of π: • Bailey–Borwein–Plouffe formula: (BBP formula) a spigot algorithm for the computation of the nth binary digit of π • Borwein's algorithm: an algorithm to calculate the value of 1/π • Chudnovsky algorithm: a fast method for calculating the digits of π • Gauss–Legendre algorithm: computes the digits of piDivision algorithms: for computing quotient and/or remainder of two numbers • Goldschmidt divisionLong divisionNewton–Raphson division: uses Newton's method to find the reciprocal of D, and multiply that reciprocal by N to find the final quotient Q. • Non-restoring divisionRestoring divisionSRT division • Exponentiation: • Addition-chain exponentiation: exponentiation by positive integer powers that requires a minimal number of multiplications • Exponentiating by squaring: an algorithm used for the fast computation of large integer powers of a number • Hyperbolic and Trigonometric Functions: • BKM algorithm: computes elementary functions using a table of logarithms • CORDIC: computes hyperbolic and trigonometric functions using a table of arctangents • Montgomery reduction: an algorithm that allows modular arithmetic to be performed efficiently when the modulus is large • Multiplication algorithms: fast multiplication of two numbers • Booth's multiplication algorithm: a multiplication algorithm that multiplies two signed binary numbers in two's complement notation • Fürer's algorithm: an integer multiplication algorithm for very large numbers possessing a very low asymptotic complexityKaratsuba algorithm: an efficient procedure for multiplying large numbers • Schönhage–Strassen algorithm: an asymptotically fast multiplication algorithm for large integers • Toom–Cook multiplication: (Toom3) a multiplication algorithm for large integers • Multiplicative inverse Algorithms: for computing a number's multiplicative inverse (reciprocal). • Newton's methodRounding functions: the classic ways to round numbers • Spigot algorithm: a way to compute the value of a mathematical constant without knowing preceding digits • Square and Nth root of a number: • Alpha max plus beta min algorithm: an approximation of the square-root of the sum of two squares • Methods of computing square rootsnth root algorithm • Summation: • Binary splitting: a divide and conquer technique which speeds up the numerical evaluation of many types of series with rational terms • Kahan summation algorithm: a more accurate method of summing floating-point numbers • Unrestricted algorithm GeometricFiltered back-projection: efficiently computes the inverse 2-dimensional Radon transform. • Level set method (LSM): a numerical technique for tracking interfaces and shapes Interpolation and extrapolationBirkhoff interpolation: an extension of polynomial interpolation • Cubic interpolationHermite interpolationLagrange interpolation: interpolation using Lagrange polynomials • Linear interpolation: a method of curve fitting using linear polynomials • Monotone cubic interpolation: a variant of cubic interpolation that preserves monotonicity of the data set being interpolated. • Multivariate interpolationBicubic interpolation: a generalization of cubic interpolation to two dimensions • Bilinear interpolation: an extension of linear interpolation for interpolating functions of two variables on a regular grid • Lanczos resampling ("Lanzosh"): a multivariate interpolation method used to compute new values for any digitally sampled data • Nearest-neighbor interpolationTricubic interpolation: a generalization of cubic interpolation to three dimensions • Pareto interpolation: a method of estimating the median and other properties of a population that follows a Pareto distribution. • Polynomial interpolationNeville's algorithmSpline interpolation: Reduces error with Runge's phenomenon. • De Boor algorithm: B-splines • De Casteljau's algorithm: Bézier curves • Trigonometric interpolation Linear algebraEigenvalue algorithms • Arnoldi iterationInverse iterationJacobi methodLanczos iterationPower iterationQR algorithmRayleigh quotient iterationGram–Schmidt process: orthogonalizes a set of vectors • Krylov methods (for large sparse matrix problems; third most-important numerical method class of the 20th century as ranked by SISC; after fast-fourier and fast-multipole) • Matrix multiplication algorithms • Cannon's algorithm: a distributed algorithm for matrix multiplication especially suitable for computers laid out in an N × N mesh • Coppersmith–Winograd algorithm: square matrix multiplicationFreivalds' algorithm: a randomized algorithm used to verify matrix multiplication • Strassen algorithm: faster matrix multiplication • Solving systems of linear equationsBiconjugate gradient method: solves systems of linear equations • Conjugate gradient: an algorithm for the numerical solution of particular systems of linear equations • Gauss–Jordan elimination: solves systems of linear equations • Gauss–Seidel method: solves systems of linear equations iteratively • Gaussian eliminationLevinson recursion: solves equation involving a Toeplitz matrixStone's method: also known as the strongly implicit procedure or SIP, is an algorithm for solving a sparse linear system of equations • Successive over-relaxation (SOR): method used to speed up convergence of the Gauss–Seidel methodTridiagonal matrix algorithm (Thomas algorithm): solves systems of tridiagonal equations • SMAWK AlgorithmSparse matrix algorithms • Cuthill–McKee algorithm: reduce the bandwidth of a symmetric sparse matrixMinimum degree algorithm: permute the rows and columns of a symmetric sparse matrix before applying the Cholesky decompositionSymbolic Cholesky decomposition: Efficient way of storing sparse matrix Monte CarloGibbs sampling: generates a sequence of samples from the joint probability distribution of two or more random variables • Hybrid Monte Carlo: generates a sequence of samples using Hamiltonian weighted Markov chain Monte Carlo, from a probability distribution which is difficult to sample directly. • Metropolis–Hastings algorithm: used to generate a sequence of samples from the probability distribution of one or more variables • Wang and Landau algorithm: an extension of Metropolis–Hastings algorithm sampling Numerical integrationMISER algorithm: Monte Carlo simulation, numerical integration Root findingBisection methodFalse position method: and Illinois method: 2-point, bracketing • Halley's method: uses first and second derivatives • ITP method: minmax optimal and superlinear convergence simultaneously • Muller's method: 3-point, quadratic interpolation • Newton's method: finds zeros of functions with calculusRidder's method: 3-point, exponential scaling • Secant method: 2-point, 1-sided Optimization algorithms Hybrid Algorithms • Alpha–beta pruning: search to reduce number of nodes in minimax algorithm • A hybrid BFGS-Like method (see more https://doi.org/10.1016/j.cam.2024.115857) • Branch and boundBruss algorithm: see odds algorithmChain matrix multiplicationCombinatorial optimization: optimization problems where the set of feasible solutions is discrete • Greedy randomized adaptive search procedure (GRASP): successive constructions of a greedy randomized solution and subsequent iterative improvements of it through a local search • Hungarian method: a combinatorial optimization algorithm which solves the assignment problem in polynomial time • Conjugate gradient methods (see more https://doi.org/10.1016/j.jksus.2022.101923) • Constraint satisfactionAC-3 algorithm general algorithms for the constraint satisfaction • Chaff algorithm: an algorithm for solving instances of the Boolean satisfiability problemDavis–Putnam algorithm: check the validity of a first-order logic formula • Difference map algorithm general algorithms for the constraint satisfaction • Davis–Putnam–Logemann–Loveland algorithm (DPLL): an algorithm for deciding the satisfiability of propositional logic formula in conjunctive normal form, i.e. for solving the CNF-SAT problem • Exact cover problem • Min conflicts algorithm general algorithms for the constraint satisfaction • Algorithm X: a nondeterministic algorithmDancing Links: an efficient implementation of Algorithm X • Cross-entropy method: a general Monte Carlo approach to combinatorial and continuous multi-extremal optimization and importance samplingDifferential evolutionDynamic Programming: problems exhibiting the properties of overlapping subproblems and optimal substructureEllipsoid method: is an algorithm for solving convex optimization problems • Evolutionary computation: optimization inspired by biological mechanisms of evolution • Evolution strategyGene expression programmingGenetic algorithmsFitness proportionate selection – also known as roulette-wheel selection • Stochastic universal samplingTournament selectionTruncation selectionMemetic algorithmSwarm intelligenceAnt colony optimizationBees algorithm: a search algorithm which mimics the food foraging behavior of swarms of honey bees • Particle swarmFrank-Wolfe algorithm: an iterative first-order optimization algorithm for constrained convex optimization • Golden-section search: an algorithm for finding the maximum of a real function • Gradient descentGrid SearchHarmony search (HS): a metaheuristic algorithm mimicking the improvisation process of musicians • A hybrid HS-LS conjugate gradient algorithm (see https://doi.org/10.1016/j.cam.2023.115304) • Interior point methodLine searchLinear programmingBenson's algorithm: an algorithm for solving linear vector optimization problems • Dantzig–Wolfe decomposition: an algorithm for solving linear programming problems with special structure • Delayed column generationInteger linear programming: solve linear programming problems where some or all the unknowns are restricted to integer values • Branch and cutCutting-plane methodKarmarkar's algorithm: The first reasonably efficient algorithm that solves the linear programming problem in polynomial time. • Simplex algorithm: an algorithm for solving linear programming problems • Local search: a metaheuristic for solving computationally hard optimization problems • Random-restart hill climbingTabu searchMinimax used in game programming • Nearest neighbor search (NNS): find closest points in a metric spaceBest Bin First: find an approximate solution to the nearest neighbor search problem in very-high-dimensional spaces • Newton's method in optimizationNonlinear optimizationBFGS method: a nonlinear optimization algorithm • Gauss–Newton algorithm: an algorithm for solving nonlinear least squares problems • Levenberg–Marquardt algorithm: an algorithm for solving nonlinear least squares problems • Nelder–Mead method (downhill simplex method): a nonlinear optimization algorithm • Odds algorithm (Bruss algorithm): Finds the optimal strategy to predict a last specific event in a random sequence event • Random SearchSimulated annealingStochastic tunnelingSubset sum algorithm ==Computational science==
Computational science
AstronomyDoomsday algorithm: day of the week • various Easter algorithms are used to calculate the day of Easter • Zeller's congruence is an algorithm to calculate the day of the week for any Julian or Gregorian calendar date BioinformaticsBasic Local Alignment Search Tool also known as BLAST: an algorithm for comparing primary biological sequence information • Bloom Filter: probabilistic data structure used to test for the existence of an element within a set. Primarily used in bioinformatics to test for the existence of a k-mer in a sequence or sequences. • Kabsch algorithm: calculate the optimal alignment of two sets of points in order to compute the root mean squared deviation between two protein structures. • Maximum parsimony (phylogenetics): an algorithm for finding the simplest phylogenetic tree to explain a given character matrix. • Sorting by signed reversals: an algorithm for understanding genomic evolution. • UPGMA: a distance-based phylogenetic tree construction algorithm. • Velvet: a set of algorithms manipulating de Bruijn graphs for genomic sequence assembly GeoscienceGeohash: a public domain algorithm that encodes a decimal latitude/longitude pair as a hash string • Vincenty's formulae: a fast algorithm to calculate the distance between two latitude/longitude points on an ellipsoid LinguisticsLesk algorithm: word sense disambiguation • Stemming algorithm: a method of reducing words to their stem, base, or root form • Sukhotin's algorithm: a statistical classification algorithm for classifying characters in a text as vowels or consonants MedicineESC algorithm for the diagnosis of heart failure • Manning Criteria for irritable bowel syndrome • Pulmonary embolism diagnostic algorithms • Texas Medication Algorithm Project PhysicsConstraint algorithm: a class of algorithms for satisfying constraints for bodies that obey Newton's equations of motion • Demon algorithm: a Monte Carlo method for efficiently sampling members of a microcanonical ensemble with a given energy • Featherstone's algorithm: computes the effects of forces applied to a structure of joints and links • Glauber dynamics: a method for simulating the Ising Model on a computer • Ground state approximation • Variational methodRitz methodn-body problemsBarnes–Hut simulation: Solves the n-body problem in an approximate way that has the order instead of as in a direct-sum simulation. • Fast multipole method (FMM): speeds up the calculation of long-ranged forces • Rainflow-counting algorithm: Reduces a complex stress history to a count of elementary stress-reversals for use in fatigue analysis • Sweep and prune: a broad phase algorithm used during collision detection to limit the number of pairs of solids that need to be checked for collision • VEGAS algorithm: a method for reducing error in Monte Carlo simulations StatisticsAlgorithms for calculating variance: avoiding instability and numerical overflow • Approximate counting algorithm: allows counting large number of events in a small register • Bayesian statisticsNested sampling algorithm: a computational approach to the problem of comparing models in Bayesian statistics • Clustering algorithmsAverage-linkage clustering: a simple agglomerative clustering algorithm • Canopy clustering algorithm: an unsupervised pre-clustering algorithm related to the K-means algorithm • Chinese whispersComplete-linkage clustering: a simple agglomerative clustering algorithm • DBSCAN: a density based clustering algorithm • Expectation-maximization algorithmFuzzy clustering: a class of clustering algorithms where each point has a degree of belonging to clusters • FLAME clustering (Fuzzy clustering by Local Approximation of MEmberships): define clusters in the dense parts of a dataset and perform cluster assignment solely based on the neighborhood relationships among objects • Fuzzy c-meansk-means clustering: cluster objects based on attributes into partitions • k-means++: a variation of this, using modified random seeds • k-medoids: similar to k-means, but chooses datapoints or medoids as centers • KHOPCA clustering algorithm: a local clustering algorithm, which produces hierarchical multi-hop clusters in static and mobile environments. • Linde–Buzo–Gray algorithm: a vector quantization algorithm to derive a good codebook • Lloyd's algorithm (Voronoi iteration or relaxation): group data points into a given number of categories, a popular algorithm for k-means clusteringOPTICS: a density based clustering algorithm with a visual evaluation method • Single-linkage clustering: a simple agglomerative clustering algorithm • SUBCLU: a subspace clustering algorithm • WACA clustering algorithm: a local clustering algorithm with potentially multi-hop structures; for dynamic networks • Ward's method: an agglomerative clustering algorithm, extended to more general Lance–Williams algorithms • Estimation TheoryExpectation-maximization algorithm A class of related algorithms for finding maximum likelihood estimates of parameters in probabilistic models • Ordered subset expectation maximization (OSEM): used in medical imaging for positron emission tomography, single-photon emission computed tomography and X-ray computed tomography. • Kalman filter: estimate the state of a linear dynamic system from a series of noisy measurements • Odds algorithm (Bruss algorithm) Optimal online search for distinguished value in sequential random input • False nearest neighbor algorithm (FNN) estimates fractal dimensionHidden Markov modelBaum–Welch algorithm: computes maximum likelihood estimates and posterior mode estimates for the parameters of a hidden Markov model • Forward–backward algorithm: a dynamic programming algorithm for computing the probability of a particular observation sequence • Viterbi algorithm: find the most likely sequence of hidden states in a hidden Markov model • Partial least squares regression: finds a linear model describing some predicted variables in terms of other observable variables • Queuing theoryBuzen's algorithm: an algorithm for calculating the normalization constant G(K) in the Gordon–Newell theoremRANSAC (an abbreviation for "RANdom SAmple Consensus"): an iterative method to estimate parameters of a mathematical model from a set of observed data which contains outliers • Scoring algorithm: is a form of Newton's method used to solve maximum likelihood equations numerically • Yamartino method: calculate an approximation to the standard deviation σθ of wind direction θ during a single pass through the incoming data • Ziggurat algorithm: generates random numbers from a non-uniform distribution ==Computer science==
Computer science
Computer architectureTomasulo algorithm: allows sequential instructions that would normally be stalled due to certain dependencies to execute non-sequentially Computer graphicsBinary space partitioningClippingLine clippingCohen–SutherlandCyrus–BeckFast-clippingLiang–BarskyNicholl–Lee–Nicholl • Polygon clipping • Sutherland–HodgmanVattiWeiler–AthertonContour lines and Isosurfaces • Marching cubes: extract a polygonal mesh of an isosurface from a three-dimensional scalar field (sometimes called voxels) • Marching squares: generates contour lines for a two-dimensional scalar field • Marching tetrahedrons: an alternative to Marching cubesDiscrete Green's theorem: an algorithm for computing double integral over a generalized rectangular domain in constant time. It is a natural extension to the summed area table algorithm • Flood fill: fills a connected region of a multi-dimensional array with a specified symbol • Global illumination algorithms: Considers direct illumination and reflection from other objects. • Ambient occlusionBeam tracingCone tracingImage-based lightingMetropolis light transportPath tracingPhoton mappingRadiosityRay tracingHidden-surface removal or visual surface determination • Newell's algorithm: eliminate polygon cycles in the depth sorting required in hidden-surface removal • Painter's algorithm: detects visible parts of a 3-dimensional scenery • Scanline rendering: constructs an image by moving an imaginary line over the image • Warnock algorithmLine drawing: graphical algorithm for approximating a line segment on discrete graphical media. • Bresenham's line algorithm: plots points of a 2-dimensional array to form a straight line between 2 specified points (uses decision variables) • DDA line algorithm: plots points of a 2-dimensional array to form a straight line between specified points • Xiaolin Wu's line algorithm: algorithm for line antialiasing. • Midpoint circle algorithm: an algorithm used to determine the points needed for drawing a circle • Ramer–Douglas–Peucker algorithm: Given a 'curve' composed of line segments to find a curve not too dissimilar but that has fewer points • ShadingGouraud shading: an algorithm to simulate the differing effects of light and colour across the surface of an object in 3D computer graphics • Phong shading: an algorithm to interpolate surface normal-vectors for surface shading in 3D computer graphics • Slerp (spherical linear interpolation): quaternion interpolation for the purpose of animating 3D rotation • Summed area table (also known as an integral image): an algorithm for computing the sum of values in a rectangular subset of a grid in constant time CryptographyAsymmetric (public key) encryption: • ElGamalElliptic curve cryptographyMAE1NTRUEncryptRSADigital signatures (asymmetric authentication): • DSA, and its variants: • ECDSA and Deterministic ECDSA • EdDSA (Ed25519) • RSACryptographic hash functions (see also the section on message authentication codes): • BLAKEMD5 – Note that there is now a method of generating collisions for MD5 • RIPEMD-160SHA-1 – Note that there is now a method of generating collisions for SHA-1 • SHA-2 (SHA-224, SHA-256, SHA-384, SHA-512) • SHA-3 (SHA3-224, SHA3-256, SHA3-384, SHA3-512, SHAKE128, SHAKE256) • Tiger (TTH), usually used in Tiger tree hashesWHIRLPOOLCryptographically secure pseudo-random number generators • Blum Blum Shub – based on the hardness of factorizationFortuna, intended as an improvement on Yarrow algorithmLinear-feedback shift register (note: many LFSR-based algorithms are weak or have been broken) • Yarrow algorithmKey exchangeDiffie–Hellman key exchangeElliptic-curve Diffie–Hellman (ECDH) • Key derivation functions, often used for password hashing and key stretchingArgon2bcryptPBKDF2scryptMessage authentication codes (symmetric authentication algorithms, which take a key as a parameter): • HMAC: keyed-hash message authentication • Poly1305SipHashSecret sharing, secret splitting, key splitting, M of N algorithms • Blakey's scheme • Shamir's secret sharingSymmetric (secret key) encryption: • Advanced Encryption Standard (AES), winner of NIST competition, also known as RijndaelBlowfishChaCha20 updated variant of Salsa20 • Data Encryption Standard (DES), sometimes DE Algorithm, winner of NBS selection competition, replaced by AES for most purposes • IDEARC4 (cipher)Salsa20ThreefishTiny Encryption Algorithm (TEA) • TwofishPost-quantum cryptographyProof-of-work algorithms Digital logic • Boolean minimization • Espresso heuristic logic minimizer: a fast algorithm for Boolean function minimization • Petrick's method: another algorithm for Boolean simplification • Quine–McCluskey algorithm: also called as Q-M algorithm, programmable method for simplifying the Boolean equations Machine learning and statistical classificationAlmeida–Pineda recurrent backpropagation: Adjust a matrix of synaptic weights to generate desired outputs given its inputs • ALOPEX: a correlation-based machine-learning algorithmAssociation rule learning: discover interesting relations between variables, used in data miningApriori algorithmEclat algorithmFP-growth algorithmOne-attribute ruleZero-attribute ruleBoosting (meta-algorithm): Use many weak learners to boost effectiveness • AdaBoost: adaptive boosting • BrownBoost: a boosting algorithm that may be robust to noisy datasets • LogitBoost: logistic regression boosting • LPBoost: linear programming boosting • Bootstrap aggregating (bagging): technique to improve stability and classification accuracy • Clustering: a class of unsupervised learning algorithms for grouping and bucketing related input vector • Computer VisionGrabcut based on Graph cutsDecision TreesC4.5 algorithm: an extension to ID3 • ID3 algorithm (Iterative Dichotomiser 3): use heuristic to generate small decision trees • k-nearest neighbors (k-NN): a non-parametric method for classifying objects based on closest training examples in the feature spaceLinde–Buzo–Gray algorithm: a vector quantization algorithm used to derive a good codebook • Locality-sensitive hashing (LSH): a method of performing probabilistic dimension reduction of high-dimensional data • Naive Bayes classifier: a family of probabilistic classifiers based on Bayes' theoremNeural NetworkBackpropagation: a supervised learning method which requires a teacher that knows, or can calculate, the desired output for any given input • Hopfield net: a Recurrent neural network in which all connections are symmetric • Perceptron: the simplest kind of feedforward neural network: a linear classifier. • Pulse-coupled neural networks (PCNN): Neural models proposed by modeling a cat's visual cortex and developed for high-performance biomimetic image processing. • Radial basis function network: an artificial neural network that uses radial basis functions as activation functions • Self-organizing map: an unsupervised network that produces a low-dimensional representation of the input space of the training samples • Random forest: classify using many decision trees • Reinforcement learning: • Q-learning: learns an action-value function that gives the expected utility of taking a given action in a given state and following a fixed policy thereafter • State–Action–Reward–State–Action (SARSA): learn a Markov decision process policy • Temporal difference learningRelevance-Vector Machine (RVM): similar to SVM, but provides probabilistic classification • Supervised learning: Learning by examples (labelled data-set split into training-set and test-set) • Support Vector Machine (SVM): a set of methods which divide multidimensional data by finding a dividing hyperplane with the maximum margin between the two sets • Structured SVM: allows training of a classifier for general structured output labels. • Winnow algorithm: related to the perceptron, but uses a multiplicative weight-update scheme Programming language theoryC3 linearization: an algorithm used primarily to obtain a consistent linearization of a multiple inheritance hierarchy in object-oriented programming • Chaitin's algorithm: a bottom-up, graph coloring register allocation algorithm that uses cost/degree as its spill metric • Hindley–Milner type inference algorithmRete algorithm: an efficient pattern matching algorithm for implementing production rule systems • Sethi-Ullman algorithm: generates optimal code for arithmetic expressions ParsingCYK algorithm: an O(n3) algorithm for parsing context-free grammars in Chomsky normal formEarley parser: another O(n3) algorithm for parsing any context-free grammarGLR parser: an algorithm for parsing any context-free grammar by Masaru Tomita. It is tuned for deterministic grammars, on which it performs almost linear time and O(n3) in worst case. • Inside-outside algorithm: an O(n3) algorithm for re-estimating production probabilities in probabilistic context-free grammars • Lexical analysisLL parser: a relatively simple linear time parsing algorithm for a limited class of context-free grammars • LR parser: A more complex linear time parsing algorithm for a larger class of context-free grammars. Variants: • Canonical LR parserLALR (look-ahead LR) parserOperator-precedence parserSimple LR parserSimple precedence parserPackrat parser: a linear time parsing algorithm supporting some context-free grammars and parsing expression grammars • Pratt parserRecursive descent parser: a top-down parser suitable for LL(k) grammars • Shunting-yard algorithm: converts an infix-notation math expression to postfix Quantum algorithmsDeutsch–Jozsa algorithm: criterion of balance for Boolean function • Grover's algorithm: provides quadratic speedup for many search problems • Shor's algorithm: provides exponential speedup (relative to currently known non-quantum algorithms) for factoring a number • Simon's algorithm: provides a provably exponential speedup (relative to any non-quantum algorithm) for a black-box problem Theory of computation and automataHopcroft's algorithm, Moore's algorithm, and Brzozowski's algorithm: algorithms for minimizing the number of states in a deterministic finite automatonPowerset construction: algorithm to convert nondeterministic automaton to deterministic automaton. • Tarski–Kuratowski algorithm: a non-deterministic algorithm which provides an upper bound for the complexity of formulas in the arithmetical hierarchy and analytical hierarchy ==Information theory and signal processing==
Information theory and signal processing
Coding theory Error detection and correctionBCH Codes • Berlekamp–Massey algorithmPeterson–Gorenstein–Zierler algorithmReed–Solomon error correctionBCJR algorithm: decoding of error correcting codes defined on trellises (principally convolutional codes) • Forward error correctionGray codeHamming codes • Hamming(7,4): a Hamming code that encodes 4 bits of data into 7 bits by adding 3 parity bits • Hamming distance: sum number of positions which are different • Hamming weight (population count): find the number of 1 bits in a binary word • Redundancy checks • Adler-32Cyclic redundancy checkDamm algorithmFletcher's checksumLongitudinal redundancy check (LRC) • Luhn algorithm: a method of validating identification numbers • Luhn mod N algorithm: extension of Luhn to non-numeric characters • Parity: simple/fast error detection technique • Verhoeff algorithm Lossless compression algorithmsBurrows–Wheeler transform: preprocessing useful for improving lossless compressionContext tree weightingDelta encoding: aid to compression of data in which sequential data occurs frequently • Dynamic Markov compression: Compression using predictive arithmetic coding • Dictionary coders • Byte pair encoding (BPE) • DeflateLempelZivLZ77 and LZ78Lempel–Ziv Jeff Bonwick (LZJB) • Lempel–Ziv–Markov chain algorithm (LZMA) • Lempel–Ziv–Oberhumer (LZO): speed oriented • Lempel–Ziv Ross Williams (LZRW) • Lempel–Ziv–Stac (LZS) • Lempel–Ziv–Storer–Szymanski (LZSS) • Lempel–Ziv–Welch (LZW) • LZWL: syllable-based variant • LZXEntropy encoding: coding scheme that assigns codes to symbols so as to match code lengths with the probabilities of the symbols • Arithmetic coding: advanced entropy coding • Range encoding: same as arithmetic coding, but looked at in a slightly different way • Huffman coding: simple lossless compression taking advantage of relative character frequencies • Adaptive Huffman coding: adaptive coding technique based on Huffman coding • Package-merge algorithm: Optimizes Huffman coding subject to a length restriction on code strings • Shannon–Fano codingShannon–Fano–Elias coding: precursor to arithmetic encoding • Entropy coding with known entropy characteristicsGolomb coding: form of entropy coding that is optimal for alphabets following geometric distributions • Rice coding: form of entropy coding that is optimal for alphabets following geometric distributions • Truncated binary encodingUnary coding: code that represents a number n with n ones followed by a zero • Universal codes: encodes positive integers into binary code words • Elias delta, gamma, and omega coding • Exponential-Golomb codingFibonacci codingLevenshtein codingFast Efficient & Lossless Image Compression System (FELICS): a lossless image compression algorithm • Incremental encoding: delta encoding applied to sequences of strings • Prediction by partial matching (PPM): an adaptive statistical data compression technique based on context modeling and prediction • Run-length encoding: lossless data compression taking advantage of strings of repeated characters • SEQUITUR algorithm: lossless compression by incremental grammar inference on a string Lossy compression algorithms3Dc: a lossy data compression algorithm for normal mapsAudio and Speech compression • A-law algorithm: standard companding algorithm • Code-excited linear prediction (CELP): low bit-rate speech compression • Linear predictive coding (LPC): lossy compression by representing the spectral envelope of a digital signal of speech in compressed form • Mu-law algorithm: standard analog signal compression or companding algorithm • Warped Linear Predictive Coding (WLPC) • Image compressionBlock Truncation Coding (BTC): a type of lossy image compression technique for greyscale images • Embedded Zerotree Wavelet (EZW) • Fast Cosine Transform algorithms (FCT algorithms): computes Discrete Cosine Transform (DCT) efficiently • Fractal compression: method used to compress images using fractals • Set Partitioning in Hierarchical Trees (SPIHT) • Wavelet compression: form of data compression well suited for image compression (sometimes also video compression and audio compression) • Transform coding: type of data compression for "natural" data like audio signals or photographic images • Vector quantization: technique often used in lossy data compression • TurboQuant: online vector quantization algorithm for lossy compression of high-dimensional vectors for LLMs • Video compression Digital signal processingAdaptive-additive algorithm (AA algorithm): find the spatial frequency phase of an observed wave source • Discrete Fourier transform: determines the frequencies contained in a (segment of a) signal • Bluestein's FFT algorithmBruun's FFT algorithmCooley–Tukey FFT algorithmFast Fourier transformPrime-factor FFT algorithmRader's FFT algorithmFast folding algorithm: an efficient algorithm for the detection of approximately periodic events within time series data • Gerchberg–Saxton algorithm: Phase retrieval algorithm for optical planes • Goertzel algorithm: identify a particular frequency component in a signal. Can be used for DTMF digit decoding. • Karplus-Strong string synthesis: physical modelling synthesis to simulate the sound of a hammered or plucked string or some types of percussion Image processingAdaptive histogram equalization: histogram equalization which adapts to local changes in contrast - Contrast Enhancement • Blind deconvolution: image de-blurring algorithm when point spread function is unknown. • Connected-component labeling: find and label disjoint regions • Dithering and half-toningError diffusionFloyd–Steinberg ditheringOrdered ditheringRiemersma dithering • Elser difference-map algorithm: a search algorithm for general constraint satisfaction problems. Originally used for X-Ray diffraction microscopy • Feature detectionCanny edge detector: detect a wide range of edges in images • Generalised Hough transformHough transformMarr–Hildreth algorithm: an early edge detection algorithm • SIFT (Scale-invariant feature transform): is an algorithm to detect and describe local features in images. • : is a robust local feature detector, first presented by Herbert Bay et al. in 2006, that can be used in computer vision tasks like object recognition or 3D reconstruction. It is partly inspired by the SIFT descriptor. The standard version of SURF is several times faster than SIFT and claimed by its authors to be more robust against different image transformations than SIFT. • Histogram equalization: use histogram to improve image contrast - Contrast Enhancement • Richardson–Lucy deconvolution: image de-blurring algorithm • Median filteringSeam carving: content-aware image resizing algorithm • Segmentation: partition a digital image into two or more regions • GrowCut algorithm: an interactive segmentation algorithm • Random walker algorithmRegion growingWatershed transformation: a class of algorithms based on the watershed analogy ==Software engineering==
Software engineering
Cache algorithmsCHS conversion: converting between disk addressing systems • Double dabble: convert binary numbers to BCD • Hash function: convert a large, possibly variable-sized amount of data into a small datum, usually a single integer that may serve as an index into an array • Fowler–Noll–Vo hash function: fast with low collision rate • Pearson hashing: computes 8-bit value only, optimized for 8-bit computers • Zobrist hashing: used in the implementation of transposition tables • Unicode collation algorithmXor swap algorithm: swaps the values of two variables without using a buffer ==Database algorithms==
Database algorithms
Distributed systems algorithms
Clock synchronizationBerkeley algorithmCristian's algorithmIntersection algorithmMarzullo's algorithmConsensus (computer science): agreeing on a single value or history among unreliable processors • Chandra–Toueg consensus algorithmPaxos algorithmRaft (computer science) • Detection of Process Termination • Dijkstra-Scholten algorithmHuang's algorithmLamport ordering: a partial ordering of events based on the happened-before relation • Leader election: a method for dynamically selecting a coordinator • Bully algorithmMutual exclusionLamport's Distributed Mutual Exclusion AlgorithmNaimi-Trehel's log(n) AlgorithmMaekawa's AlgorithmRaymond's AlgorithmRicart–Agrawala AlgorithmSnapshot algorithm: record a consistent global state for an asynchronous system • Chandy–Lamport algorithmVector clocks: generate a partial ordering of events in a distributed system and detect causality violations Memory allocation and deallocation algorithmsBuddy memory allocation: an algorithm to allocate memory such with less fragmentation • Garbage collectorsCheney's algorithm: an improvement on the Semi-space collectorGenerational garbage collector: Fast garbage collectors that segregate memory by age • Mark-compact algorithm: a combination of the mark-sweep algorithm and Cheney's copying algorithmMark and sweepSemi-space collector: an early copying collector • Reference counting ==Networking==
Networking
Karn's algorithm: addresses the problem of getting accurate estimates of the round-trip time for messages when using TCP • Luleå algorithm: a technique for storing and searching internet routing tables efficiently • Network congestionExponential backoffNagle's algorithm: improve the efficiency of TCP/IP networks by coalescing packets • Truncated binary exponential backoff ==Operating systems algorithms==
Operating systems algorithms
Banker's algorithm: algorithm used for deadlock avoidance • Page replacement algorithms: for selecting the victim page under low memory conditions • Adaptive replacement cache: better performance than LRU • Clock with Adaptive Replacement (CAR): a page replacement algorithm with performance comparable to adaptive replacement cache Process synchronizationDekker's algorithmLamport's Bakery algorithmPeterson's algorithm SchedulingEarliest deadline first schedulingFair-share schedulingLeast slack time schedulingList schedulingMulti level feedback queueRate-monotonic schedulingRound-robin schedulingShortest job nextShortest remaining timeTop-nodes algorithm: resource calendar management I/O scheduling Disk schedulingElevator algorithm: Disk scheduling algorithm that works like an elevator. • Shortest seek first: Disk scheduling algorithm to reduce seek time. ==See also==
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