optimization, the criss-cross algorithm is any of a family of algorithms for linear programming. Variants of the criss-cross algorithm also solve more general...

crossings can be colloquially referred to "criss-crosses" Criss-cross algorithm, a basis-exchange pivoting algorithm for linear programming (and more general...

simplex algorithm or by the criss-cross algorithm. Pivoting rule of Bland, which avoids cycling Criss-cross algorithm Cutting-plane method Devex algorithm Fourier–Motzkin...

simplex algorithm of Dantzig, the criss-cross algorithm is a basis-exchange algorithm that pivots between bases. However, the criss-cross algorithm need...

oriented matroids" by Jack Edmonds. Another pivoting rule, the criss-cross algorithm, avoids cycles on all oriented-matroid linear-programs. Bland (1977)...

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

the simplex algorithm and the criss-cross algorithm visit all 8 corners in the worst case. In particular, many optimization algorithms for linear optimization...

shrink the simplex towards a better point. An intuitive explanation of the algorithm from "Numerical Recipes": The downhill simplex method now takes a series...

can be solved also by the criss-cross algorithm, conversely, for linear complementarity problems, the criss-cross algorithm terminates finitely only if...

an algorithm design paradigm for discrete and combinatorial optimization problems, as well as mathematical optimization. A branch-and-bound algorithm consists...

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...

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...

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...

linear programming problems using the simplex algorithm. The Big M method extends the simplex algorithm to problems that contain "greater-than" constraints...

method or quasi-Newton methods like the Broyden–Fletcher–Goldfarb–Shanno algorithm. The approach has been applied to solve a wide range of problems, including...

method, named after Isaac Newton and Joseph Raphson, is a root-finding algorithm which produces successively better approximations to the roots (or zeroes)...

designed to find, generate, tune, or select a heuristic (partial search algorithm) that may provide a sufficiently good solution to an optimization problem...

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...

computer science and operations research, the bees algorithm is a population-based search algorithm which was developed by Pham, Ghanbarzadeh et al. in...

The Frank–Wolfe algorithm is an iterative first-order optimization algorithm for constrained convex optimization. Also known as the conditional gradient...

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

computer science and operations research, approximation algorithms are efficient algorithms that find approximate solutions to optimization problems...

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}...

technique which belongs to the family of local search. It is an iterative algorithm that starts with an arbitrary solution to a problem, then attempts to...

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

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...

science and operations research, the artificial bee colony algorithm (ABC) is an optimization algorithm based on the intelligent foraging behaviour of honey...

tractable, and so specialized algorithms that quickly rule out large parts of the search space or approximation algorithms must be resorted to instead....

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...

of the simplex algorithm that are especially suited for network optimization Combinatorial algorithms Quantum optimization algorithms The iterative methods...