static problems in this context and solved by static algorithms) have meaningful dynamic versions. Incremental algorithms, or online algorithms, are algorithms...

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

complex algorithms, there has been substantial research on creating and analyzing algorithms that approximate a solution. The knapsack problem, though...

well-known algorithms exist for solving this problem and its variants. Dijkstra's algorithm solves the single-source shortest path problem with only non-negative...

Needleman–Wunsch algorithm is an algorithm used in bioinformatics to align protein or nucleotide sequences. It was one of the first applications of dynamic programming...

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

Dynamic programming is both a mathematical optimization method and an algorithmic paradigm. The method was developed by Richard Bellman in the 1950s and...

First). It is also employed as a subroutine in algorithms such as Johnson's algorithm. The algorithm uses a min-priority queue data structure for selecting...

AC-3 algorithm, which enforces arc consistency. Local search methods are incomplete satisfiability algorithms. They may find a solution of a problem, but...

for Exponential-Time Dynamic Programming Algorithms". Proceedings of the Thirtieth Annual ACM-SIAM Symposium on Discrete Algorithms. pp. 1783–1793. doi:10...

Although this problem can be solved using several different algorithmic techniques, including brute force, divide and conquer, dynamic programming, and...

Page replacement algorithm Algorithms for calculating variance Ukkonen's algorithm A problem exemplifying the concepts of online algorithms is the Canadian...

In time series analysis, dynamic time warping (DTW) is an algorithm for measuring similarity between two temporal sequences, which may vary in speed. For...

Differential evolution Dynamic relaxation Evolutionary algorithms Genetic algorithms Hill climbing with random restart Memetic algorithm Nelder–Mead simplicial...

applications in parsing algorithms for natural languages and in training algorithms for conditional random fields. The dynamic MST problem concerns the update...

many reinforcement learning algorithms use dynamic programming techniques. The main difference between classical dynamic programming methods and reinforcement...

polynomial time dynamic programming algorithm. However, the exponent of the polynomial depends on the clique-width of the graph, so this algorithms is not fixed-parameter...

study of the computational complexity of geometric algorithms. Randomized algorithms that solve the problem in linear time are known, in Euclidean spaces whose...

the problem can be produced with sophisticated algorithms. In addition, many approximation algorithms exist. For example, the first fit algorithm provides...

efficient algorithms. It was the key, for example, to Karatsuba's fast multiplication method, the quicksort and mergesort algorithms, the Strassen algorithm for...

algorithms (also known as force-directed algorithms or spring-based algorithm) Spectral layout Network analysis Link analysis Girvan–Newman algorithm:...

approximation algorithms are efficient algorithms that find approximate solutions to optimization problems (in particular NP-hard problems) with provable...

is still the fastest. Also, a dynamic programming algorithm of Bellman, Held, and Karp can be used to solve the problem in time O(n2 2n). In this method...

Evolutionary algorithms (EA) reproduce essential elements of biological evolution in a computer algorithm in order to solve "difficult" problems, at least...

algorithms (EA). Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems via biologically inspired...

closed. Algorithm A is optimally efficient with respect to a set of alternative algorithms Alts on a set of problems P if for every problem P in P and...

index. Early algorithms for online approximate matching were suggested by Wagner and Fischer and by Sellers. Both algorithms are based on dynamic programming...

algorithms based on greedy algorithm, dynamic programming can give a relatively “good” solution to the 0-1 QKP efficiently. The brute-force algorithm...

of algorithms that can be stated in terms of geometry. Some purely geometrical problems arise out of the study of computational geometric algorithms, and...

input sequences, the problem is NP-hard. When the number of sequences is constant, the problem is solvable in polynomial time by dynamic programming. Given...