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Sequence of locally optimal choices
A greedy algorithm is an algorithm which, at each step, makes the choice that is locally optimal, and subsequently does not reconsider past choices. Greedy
Greedy_algorithm
Method for finding sums of unit fractions
In mathematics, the greedy algorithm for Egyptian fractions is a greedy algorithm, first described by Fibonacci, for transforming rational numbers into
Greedy algorithm for Egyptian fractions
Greedy_algorithm_for_Egyptian_fractions
One-by-one assignment of colors to graph vertices
computer science, a greedy coloring or sequential coloring is a coloring of the vertices of a graph formed by a greedy algorithm that considers the vertices
Greedy_coloring
Algorithm for finding shortest paths
target. The process that underlies Dijkstra's algorithm is similar to the greedy process used in Prim's algorithm. Prim's purpose is to find a minimum spanning
Dijkstra's_algorithm
Minimum spanning forest algorithm that greedily adds edges
It is a greedy algorithm that in each step adds to the forest the lowest-weight edge that will not form a cycle. The key steps of the algorithm are sorting
Kruskal's_algorithm
Classical problem in combinatorics
1 {\displaystyle \ln \Delta +1} of the greedy algorithm essentially tight in this case. The greedy algorithm for the weighted set cover problem directly
Set_cover_problem
Algorithm for the travelling salesman problem
Gutin and A. Yeo, When the greedy algorithm fails. Discrete Optimization 1 (2004), 121–127. G. Bendall and F. Margot, Greedy Type Resistance of Combinatorial
Nearest_neighbour_algorithm
Algorithm used for pathfinding and graph traversal
Informational search with online learning. A* differs from a greedy best-first search algorithm in that it takes the cost/distance already traveled, g(n)
A*_search_algorithm
Problem in computer science
essentially matches the approximation ratio achieved by the generic greedy algorithm used for maximization of submodular functions with a cardinality constraint
Maximum_coverage_problem
Resource problem in machine learning
values. Explore-then-commit algorithm Gittins index – a powerful, general strategy for analyzing bandit problems. Greedy algorithm Optimal stopping Search
Multi-armed_bandit
Decision tree algorithm
3) is a greedy algorithm invented by Ross Quinlan used to generate a decision tree from a dataset. ID3 is the precursor to the C4.5 algorithm. The 3 in
ID3_algorithm
Machine-learning process
correspond to a sentence non-terminal. Like all greedy algorithms, greedy grammar inference algorithms make, in iterative manner, decisions that seem to
Grammar_induction
Combinatorial optimization problem
overall the algorithm takes O ( n k ) {\displaystyle {\mathcal {O}}(nk)} time. The solution obtained using the simple greedy algorithm is a 2-approximation
Metric_k-center
Algorithm in computer science
science and operations research, the artificial bee colony algorithm (ABC) is an optimization algorithm based on the intelligent foraging behaviour of honey
Artificial bee colony algorithm
Artificial_bee_colony_algorithm
Search algorithm or heuristic method to solve constraint satisfaction problems
not specified in the algorithm, a good initial assignment can be critical for quickly approaching a solution. Use a greedy algorithm with some level of
Min-conflicts_algorithm
Algorithm to compute the maximum flow in a network
Ford–Fulkerson algorithm (FFA) is a greedy algorithm that computes the maximum flow in a flow network. It is sometimes called a "method" instead of an "algorithm" as
Ford–Fulkerson_algorithm
Optimization algorithm
the feasible set, which has helped to the popularity of the algorithm for sparse greedy optimization in machine learning and signal processing problems
Frank–Wolfe_algorithm
Optimization by removing non-optimal solutions to subproblems
an algorithm design paradigm for discrete and combinatorial optimization problems, as well as mathematical optimization. A branch-and-bound algorithm consists
Branch_and_bound
Class of greedy algorithms for multiway number partitioning
computer science, greedy number partitioning is a class of greedy algorithms for multiway number partitioning. The input to the algorithm is a set S of numbers
Greedy_number_partitioning
Collection of subsets covering all t-element subsets
{\displaystyle t} -subsets are covered. This approach is analogous to the greedy algorithm of Conway and Sloane for constructing lexicographic codes. The list
Covering_design
Choosing the fewest coins to make a given amount of money
the greedy chooses seven coins (25, 10, and 5 × 1), but the optimal is four (4 × 10). A coin system is called "canonical" if the greedy algorithm always
Change-making_problem
Topics referred to by the same term
Look up greedy in Wiktionary, the free dictionary. Someone who is greedy is consumed with selfish desires. Greedy may also refer to: Greedy (album), an
Greedy
no code word is longer than L. It is a greedy algorithm, and a generalization of Huffman's original algorithm. Package-merge works by reducing the code
Package-merge_algorithm
Optimization algorithm
currentPoint Contrast genetic algorithm; random optimization. Gradient descent Greedy algorithm Tâtonnement Mean-shift A* search algorithm Russell, Stuart J.; Norvig
Hill_climbing
Method for finding minimum spanning trees
Borůvka's algorithm is a greedy algorithm for finding a minimum spanning tree in a graph, or a minimum spanning forest in the case of a graph that is
Borůvka's_algorithm
Type of graph related to pursuit–evasion
vertex. The cop-win graphs can be recognized in polynomial time by a greedy algorithm that constructs a dismantling order. They include the chordal graphs
Cop-win_graph
Sequence of operations for a task
of greedy algorithms is finding minimal spanning trees of graphs without negative cycles. Huffman Tree, Kruskal, Prim, Sollin are greedy algorithms that
Algorithm
are two famous algorithms to achieve asymptotically optimal packing in k-uniform hypergraphs. One of them is a random greedy algorithm which was proposed
Packing_in_a_hypergraph
Graph exploring search algorithm
a greedy best-first search, as they incorporate the distance from the start in addition to estimated distances to the goal. Using a greedy algorithm, expand
Best-first_search
Methodic assignment of colors to elements of a graph
called sequential coloring algorithms. The maximum (worst) number of colors that can be obtained by the greedy algorithm, by using a vertex ordering
Graph_coloring
Subfield of mathematical optimization
limited search window) and tabu search (a greedy-type swapping algorithm). However, generic search algorithms are not guaranteed to find an optimal solution
Combinatorial_optimization
Method for finding minimum spanning trees
In computer science, Prim's algorithm is a greedy algorithm that finds a minimum spanning tree for a weighted undirected graph. This means it finds a
Prim's_algorithm
Algorithm that begins on possibly incomplete inputs
Some online algorithms: Insertion sort Perceptron Reservoir sampling Greedy algorithm Odds algorithm Page replacement algorithm Algorithms for calculating
Online_algorithm
Algorithm for job scheduling
Longest-processing-time-first (LPT) is a greedy algorithm for job scheduling. The input to the algorithm is a set of jobs, each of which has a specific
Longest-processing-time-first scheduling
Longest-processing-time-first_scheduling
The greedy triangulation is a method to compute a polygon triangulation or a point set triangulation using a greedy algorithm, which adds edges one by
Greedy_triangulation
Polynomial-time algorithm for the assignment problem
The Hungarian algorithm or Hungarian method is a combinatorial optimization algorithm that solves the assignment problem in polynomial time and which
Hungarian_algorithm
Algorithm to compute the maximum flow in a flow network
In computer science, the Edmonds–Karp algorithm is an implementation of the Ford–Fulkerson method for computing the maximum flow in a flow network in
Edmonds–Karp_algorithm
Overview of and topical guide to algorithms
problems with overlapping subproblems and optimal substructure Greedy algorithm — algorithm that makes locally optimal choices Backtracking — search technique
Outline_of_algorithms
Population-based search algorithm
computer science and operations research, the bees algorithm is a population-based search algorithm which was developed by Pham, Ghanbarzadeh et al. in
Bees_algorithm
Optimization algorithm
computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems
Ant colony optimization algorithms
Ant_colony_optimization_algorithms
Sequential model-based optimization of expensive black-box functions
and William J. Welch introduced the efficient global optimization (EGO) algorithm, which used a kriging or Gaussian-process model with expected improvement
Bayesian_optimization
Greedy algorithm
List scheduling is a greedy algorithm for Identical-machines scheduling. The input to this algorithm is a list of jobs that should be executed on a set
List_scheduling
Algorithm for finding zeros of functions
method, named after Isaac Newton and Joseph Raphson, is a root-finding algorithm which produces successively better approximations to the roots (or zeroes)
Newton's_method
Type of algorithm, produces approximately correct solutions
for even a moderate size problem is difficult to solve. Instead, the greedy algorithm can be used to give a good but not optimal solution (it is an approximation
Heuristic_(computer_science)
Minimum spanning forest algorithm that greedily deletes edges
This algorithm is a greedy algorithm, choosing the best choice given any situation. It is the reverse of Kruskal's algorithm, which is another greedy algorithm
Reverse-delete_algorithm
Numerical method for solving boundary value problems
solution can be approximated as a separate representation and a numerical greedy algorithm to find the solution. In the Proper Generalized Decomposition method
Proper generalized decomposition
Proper_generalized_decomposition
for mobile ad-hoc networks. It was developed by B. Karp. It uses a greedy algorithm to do the routing and orbits around a perimeter. GPSR is a geo routing
Greedy Perimeter Stateless Routing in Wireless Networks
Greedy_Perimeter_Stateless_Routing_in_Wireless_Networks
Optimization algorithm
an optimization algorithm in the collection of quasi-Newton methods that approximates the Broyden–Fletcher–Goldfarb–Shanno algorithm (BFGS) using a limited
Limited-memory_BFGS
Algorithm for computing the maximal flow of a network
Dinic's algorithm or Dinitz's algorithm is a strongly polynomial algorithm for computing the maximum flow in a flow network, conceived in 1970 by Israeli
Dinic's_algorithm
Optimization method
In numerical optimization, the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm is an iterative method for solving unconstrained nonlinear optimization
Broyden–Fletcher–Goldfarb–Shanno algorithm
Broyden–Fletcher–Goldfarb–Shanno_algorithm
Algorithm for linear programming
optimization, Dantzig's simplex algorithm (or simplex method) is an algorithm for linear programming. The name of the algorithm is derived from the concept
Simplex_algorithm
Metaheuristic proposed by Xin-She Yang
firefly algorithm is a metaheuristic proposed by Xin-She Yang and inspired by the flashing behavior of fireflies. In pseudocode the algorithm can be stated
Firefly_algorithm
Algorithm used to solve non-linear least squares problems
In mathematics and computing, the Levenberg–Marquardt algorithm (LMA or just LM), also known as the damped least-squares (DLS) method, is used to solve
Levenberg–Marquardt_algorithm
Feature of continuing on a new line when a line is full
needs to be optimized for, different algorithms are used. A simple way to do word wrapping is to use a greedy algorithm that puts as many words on a line
Wrapping_(text)
Heuristic algorithm for finding partitions of graphs
assigning weight one to each edge. The algorithm maintains and improves a partition, in each pass using a greedy algorithm to pair up vertices of A with vertices
Kernighan–Lin_algorithm
Mathematical optimization problem restricted to integers
Branch and bound algorithms have a number of advantages over algorithms that only use cutting planes. One advantage is that the algorithms can be terminated
Integer_programming
Type of randomized algorithm
In computing, a Las Vegas algorithm is a randomized algorithm that always gives correct results; that is, it always produces the correct result or it
Las_Vegas_algorithm
Problem optimization method
Mathematics portal Convexity in economics – Significant topic in economics Greedy algorithm – Sequence of locally optimal choices Non-convexity (economics) – Violations
Dynamic_programming
Class of algorithms that find approximate solutions to optimization problems
established techniques to design approximation algorithms. These include the following ones. Greedy algorithm Local search Enumeration and dynamic programming
Approximation_algorithm
Optimization algorithm
unconstrained mathematical optimization. It is a first-order iterative algorithm for minimizing a differentiable multivariate function. The idea is to
Gradient_descent
maximum welfare can be approximated by the following polynomial-time greedy algorithm: Initialize X1 = X2 = ... = Xn = empty. For every item g (in an arbitrary
Welfare_maximization
Heuristic search algorithm
number of best partial solutions are kept as candidates. It is thus a greedy algorithm. Beam search uses breadth-first search to build its search tree. At
Beam_search
Line-breaking algorithm used in the TeX typesetting package
Methods to do this include the SMAWK algorithm. For the input text AAA BB CC DDDDD with line width 6, a greedy algorithm that puts as many words on a line
Knuth–Plass line-breaking algorithm
Knuth–Plass_line-breaking_algorithm
Method to solve optimization problems
affine (linear) function defined on this polytope. A linear programming algorithm finds a point in the polytope where this function has the largest (or
Linear_programming
Technique or strategy underlying a variety of algorithms
conquer Dynamic programming Greedy algorithm Recursion Prune and search Kernelization Iterative compression Sweep line algorithms Rotating calipers Randomized
Algorithmic_paradigm
Problem in combinatorial optimization
time approximation scheme (FPTAS). George Dantzig proposed a greedy approximation algorithm to solve the unbounded knapsack problem. His version sorts the
Knapsack_problem
point per y coordinate), is known to be NP-complete. The following greedy algorithm constructs arborally satisfiable sets: Sweep the point set with a horizontal
Geometry of binary search trees
Geometry_of_binary_search_trees
Combinatorial optimization method
to integer values. Branch and cut involves running a branch and bound algorithm and using cutting planes to tighten the linear programming relaxations
Branch_and_cut
Computer compiler optimization technique
to the graph, along with its edges, and make a greedy choice for the new vertex's allocation. This greedy allocation uses the same method as outlined in
Register_allocation
Study of mathematical algorithms for optimization problems
of the simplex algorithm that are especially suited for network optimization Combinatorial algorithms Quantum optimization algorithms The iterative methods
Mathematical_optimization
Combinatorial optimization problem
i return S Line 1: This algorithm is called Greedy-Iterative-Activity-Selector, because it is first of all a greedy algorithm, and then it is iterative
Activity_selection_problem
Metaheuristic commonly used for optimization problems
The greedy randomized adaptive search procedure (also known as GRASP) is a metaheuristic algorithm commonly applied to combinatorial optimization problems
Greedy randomized adaptive search procedure
Greedy_randomized_adaptive_search_procedure
Finite sum of distinct unit fractions
sometimes Fibonacci's greedy algorithm is attributed to James Joseph Sylvester. After his description of the greedy algorithm, Fibonacci suggests yet
Egyptian_fraction
Mathematical algorithm
optimization algorithm that successively minimizes along coordinate directions to find the minimum of a function. At each iteration, the algorithm determines
Coordinate_descent
Linear programming algorithm
Karmarkar's algorithm is an algorithm introduced by Narendra Karmarkar in 1984 for solving linear programming problems. It was the first reasonably efficient
Karmarkar's_algorithm
Numerical optimization algorithm
shrink the simplex towards a better point. An intuitive explanation of the algorithm from "Numerical Recipes": The downhill simplex method now takes a series
Nelder–Mead_method
an odd greedy expansion? More unsolved problems in mathematics In number theory, the odd greedy expansion problem asks whether a greedy algorithm for finding
Odd_greedy_expansion
NP-complete problem in computer science
can be solved by algorithms developed for each of these problems. Algorithms developed for multiway number partitioning include: Greedy number partitioning
Partition_problem
Optimization technique
designed to find, generate, tune, or select a heuristic (partial search algorithm) that may provide a sufficiently good solution to an optimization problem
Metaheuristic
Optimizing objective functions that have constrained variables
COP is a CSP that includes an objective function to be optimized. Many algorithms are used to handle the optimization part. A general constrained minimization
Constrained_optimization
Concept in computational geometry
of shapes, an approximation to MDS(C) can be found by the following greedy algorithm: INITIALIZATION: Initialize an empty set, S. SEARCH: For every shape
Maximum_disjoint_set
Numerical approximation algorithm
hill climbing, Newton's method, or quasi-Newton methods like BFGS, is an algorithm of an iterative method or a method of successive approximation. An iterative
Iterative_method
Collective behavior of decentralized, self-organized systems
swarm robotics while swarm intelligence refers to the more general set of algorithms. Swarm prediction has been used in the context of forecasting problems
Swarm_intelligence
Method of solving linear programming problems
linear programming problems using the simplex algorithm. The Big M method extends the simplex algorithm to problems that contain "greater-than" constraints
Big_M_method
Property of a computational problem
property is used to determine the usefulness of greedy algorithms for a problem. Typically, a greedy algorithm is used to solve a problem with optimal substructure
Optimal_substructure
Inequalities for inexact line search
+ {\displaystyle \alpha \in \mathbb {R} ^{+}} exactly. A line search algorithm can use Wolfe conditions as a requirement for any guessed α {\displaystyle
Wolfe_conditions
Three tangent circles in a triangle
Malfatti circles. Instead, the optimal solution can always be found by a greedy algorithm that finds the largest circle within the given triangle, the largest
Malfatti_circles
Technique for finding an extremum of a function
but very robust. The technique derives its name from the fact that the algorithm maintains the function values for four points whose three interval widths
Golden-section_search
Set system used in greedy optimization
solved by greedy algorithms. Around 1980, Korte and Lovász introduced the greedoid to further generalize this characterization of greedy algorithms; hence
Greedoid
Machine learning algorithm
of top-down induction of decision trees (TDIDT) is an example of a greedy algorithm, and it is by far the most common strategy for learning decision trees
Decision_tree_learning
Numerical optimization algorithm
Berndt–Hall–Hall–Hausman (BHHH) algorithm is a numerical optimization algorithm similar to the Newton–Raphson algorithm, but it replaces the observed negative
Berndt–Hall–Hall–Hausman algorithm
Berndt–Hall–Hall–Hausman_algorithm
Local search algorithm
simulated annealing, genetic algorithms, ant colony optimization algorithms, reactive search optimization, guided local search, or greedy randomized adaptive search
Tabu_search
Optimization algorithm
f(\mathbf {x} _{k+1})\|<\epsilon } At the line search step (2.3), the algorithm may minimize h exactly, by solving h ′ ( α k ) = 0 {\displaystyle h'(\alpha
Line_search
Travelling salesman problem heuristic
problems). This algorithm is also sometimes called the "greedy algorithm" for the TSP. The algorithm builds a tour for the traveling salesman one edge at
Multi-fragment_algorithm
Analysis and representation of complex networks
unique minimal power graph of minimal nesting level. The power graph greedy algorithm relies on two simple steps to perform the decomposition: The first
Power_graph_analysis
Mathematical sequence involving arithmetic progressions
mathematics, a Stanley sequence is an integer sequence generated by a greedy algorithm that chooses the sequence members to avoid arithmetic progressions
Stanley_sequence
Graph colouring algorithm by Daniel Brélaz
DSatur is a graph colouring algorithm put forward by Daniel Brélaz in 1979. Similarly to the greedy colouring algorithm, DSatur colours the vertices of
DSatur
Unrelated vertices in graphs
approximation algorithms are known with approximation ratios that are constant for a fixed value of the maximum degree; for instance, a greedy algorithm that forms
Independent set (graph theory)
Independent_set_(graph_theory)
Class of algorithms for solving constrained optimization problems
Augmented Lagrangian methods are a certain class of algorithms for solving constrained optimization problems. They have similarities to penalty methods
Augmented_Lagrangian_method
Form of public key cryptography
the problem is "easy" and solvable in polynomial time with a simple greedy algorithm. In Merkle–Hellman, decrypting a message requires solving an apparently
Merkle–Hellman knapsack cryptosystem
Merkle–Hellman_knapsack_cryptosystem
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