push–relabel algorithm (alternatively, preflow–push algorithm) is an algorithm for computing maximum flows in a flow network. The name "push–relabel"...

flow algorithm of Dinitz; the push-relabel algorithm of Goldberg and Tarjan; and the binary blocking flow algorithm of Goldberg and Rao. The algorithms of...

science, the Edmonds–Karp algorithm is an implementation of the Ford–Fulkerson method for computing the maximum flow in a flow network in O ( | V | | E...

minimum-cost flow: 326–331  The push–relabel maximum flow algorithm, one of the most efficient known techniques for maximum flow Otherwise the problem can be...

|V|}}}\right)} . Their algorithm is based on using a push-relabel maximum flow algorithm and then, when the matching created by this algorithm becomes close to...

nodes. As such, efficient algorithms for solving network flows can also be applied to solve problems that can be reduced to a flow network, including survey...

of the push-relabel algorithm. Network simplex algorithm: a specialized version of the linear programming simplex method. Out-of-kilter algorithm by D....

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...

Blum Shub proposed by L. Blum, M. Blum, and M. Shub 1986 – Push relabel maximum flow algorithm by Andrew Goldberg and Robert Tarjan 1986 – Barnes–Hut tree...

generality, since one can find the maximum value of f(x) by finding the minimum of g(x) = −f(x). A B&B algorithm operates according to two principles:...

In numerical optimization, the Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm is an iterative method for solving unconstrained nonlinear optimization...

or polytope method) is a numerical method used to find the minimum or maximum of an objective function in a multidimensional space. It is a direct search...

Parallel Algorithms for Graph Matching Problems, Oxford University Press, ISBN 978-0-19-850162-6 A graph library with Hopcroft–Karp and Push–Relabel-based...

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...

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...

h(x_{k})^{T}d\geq 0\\&g(x_{k})+\nabla g(x_{k})^{T}d=0.\end{array}}} The SQP algorithm starts from the initial iterate ( x 0 , λ 0 , σ 0 ) {\displaystyle (x_{0}...

computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems...

practice. These algorithms are called auction algorithms, push-relabel algorithms, or preflow-push algorithms. Some of these algorithms were shown to be...

as network flow problems and multicommodity flow problems, are considered important enough to have much research on specialized algorithms. A number of...

Dantzig's simplex algorithm (or simplex method) is a popular algorithm for linear programming.[failed verification] The name of the algorithm is derived from...

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

an optimization algorithm in the collection of quasi-Newton methods that approximates the Broyden–Fletcher–Goldfarb–Shanno algorithm (BFGS) using a limited...

A greedy algorithm is any algorithm that follows the problem-solving heuristic of making the locally optimal choice at each stage. In many problems, a...

[CGR96][GH05] including the discovery of the push–relabel maximum flow algorithm.[GT88] He also worked on algorithmic game theory, where he was one of the first...

Kapoor, S; Vaidya, P M (1986-11-01). "Fast algorithms for convex quadratic programming and multicommodity flows". Proceedings of the eighteenth annual ACM...

a mathematical algorithm for eliminating variables from a system of linear inequalities. It can output real solutions. The algorithm is named after Joseph...

IPMs) are algorithms for solving linear and non-linear convex optimization problems. IPMs combine two advantages of previously-known algorithms: Theoretically...

Greedy algorithm Integer programming Branch and bound/cut Graph algorithms Network flows Dinic Edmonds–Karp Ford–Fulkerson Push–relabel maximum flow...

problem using the max-flow min-cut theorem and a polynomial time algorithm for maximum flow, such as the push-relabel algorithm, though this approach...

Augmented Lagrangian methods are a certain class of algorithms for solving constrained optimization problems. They have similarities to penalty methods...