annealing algorithm
2Algorithm — Flow chart of an algorithm (Euclid s algorithm) for calculating the greatest common divisor (g.c.d.) of two numbers a and b in locations named A and B. The algorithm proceeds by successive subtractions in two loops: IF the test B ≤ A yields yes… …
3Simulated annealing — (SA) is a generic probabilistic meta algorithm for the global optimization problem, namely locating a good approximation to the global optimum of a given function in a large search space. It is often used when the search space is discrete (e.g.,… …
4Genetic algorithm — A genetic algorithm (GA) is a search heuristic that mimics the process of natural evolution. This heuristic is routinely used to generate useful solutions to optimization and search problems. Genetic algorithms belong to the larger class of… …
5Adaptive simulated annealing — (ASA) is a variant of simulated annealing (SA) algorithm in which the algorithm parameters that control temperature schedule and random step selection are automatically adjusted according to algorithm progress. This makes the algorithm more… …
6Criss-cross algorithm — This article is about an algorithm for mathematical optimization. For the naming of chemicals, see crisscross method. The criss cross algorithm visits all 8 corners of the Klee–Minty cube in the worst case. It visits 3 additional… …
7Quantum annealing — In mathematics and applications, quantum annealing (QA) is a general method for finding the global minimum of a given objective function over a given set of candidate solutions (the search space ), by a process analogous to quantum fluctuations.… …
8Expectation-maximization algorithm — An expectation maximization (EM) algorithm is used in statistics for finding maximum likelihood estimates of parameters in probabilistic models, where the model depends on unobserved latent variables. EM alternates between performing an… …
9Levenberg–Marquardt algorithm — In mathematics and computing, the Levenberg–Marquardt algorithm (LMA)[1] provides a numerical solution to the problem of minimizing a function, generally nonlinear, over a space of parameters of the function. These minimization problems arise… …
10Deutsch–Jozsa algorithm — The Deutsch–Jozsa algorithm is a quantum algorithm, proposed by David Deutsch and Richard Jozsa in 1992[1] with improvements by Richard Cleve, Artur Ekert, Chiara Macchiavello, and Michele Mosca in 1998.[2] Although it is of little practical use …
