Faster access than browser!
32 relations: Algorithm, Arkadi Nemirovski, Augmented Lagrangian method, Barrier function, Cambridge University Press, Convex optimization, Convex set, Diagonal matrix, Ellipsoid method, Epigraph (mathematics), Feasible region, Gradient, Hessian matrix, Iteration, Jacobian matrix and determinant, John von Neumann, Karmarkar's algorithm, Karush–Kuhn–Tucker conditions, Lagrange multiplier, Leonid Khachiyan, Linear function, Linear programming, Mehrotra predictor–corrector method, Narendra Karmarkar, Newton's method, Nonlinear programming, Penalty method, Self-concordant function, Sequential quadratic programming, Simplex algorithm, Time complexity, Yurii Nesterov.
Algorithm
In mathematics and computer science, an algorithm is an unambiguous specification of how to solve a class of problems.
New!!: Interior-point method and Algorithm · See more »
Arkadi Nemirovski
Arkadi Nemirovski (born March 14, 1947) is a professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Institute of Technology.
New!!: Interior-point method and Arkadi Nemirovski · See more »
Augmented Lagrangian method
Augmented Lagrangian methods are a certain class of algorithms for solving constrained optimization problems.
New!!: Interior-point method and Augmented Lagrangian method · See more »
Barrier function
In constrained optimization, a field of mathematics, a barrier function is a continuous function whose value on a point increases to infinity as the point approaches the boundary of the feasible region of an optimization problem.
New!!: Interior-point method and Barrier function · See more »
Cambridge University Press
Cambridge University Press (CUP) is the publishing business of the University of Cambridge.
New!!: Interior-point method and Cambridge University Press · See more »
Convex optimization
Convex optimization is a subfield of optimization that studies the problem of minimizing convex functions over convex sets.
New!!: Interior-point method and Convex optimization · See more »
Convex set
In convex geometry, a convex set is a subset of an affine space that is closed under convex combinations.
New!!: Interior-point method and Convex set · See more »
Diagonal matrix
In linear algebra, a diagonal matrix is a matrix in which the entries outside the main diagonal are all zero.
New!!: Interior-point method and Diagonal matrix · See more »
Ellipsoid method
In mathematical optimization, the ellipsoid method is an iterative method for minimizing convex functions.
New!!: Interior-point method and Ellipsoid method · See more »
Epigraph (mathematics)
In mathematics, the epigraph or supergraph of a function f: Rn→R is the set of points lying on or above its graph: The strict epigraph is the epigraph with the graph itself removed: The same definitions are valid for a function that takes values in R ∪ ∞.
New!!: Interior-point method and Epigraph (mathematics) · See more »
Feasible region
In mathematical optimization, a feasible region, feasible set, search space, or solution space is the set of all possible points (sets of values of the choice variables) of an optimization problem that satisfy the problem's constraints, potentially including inequalities, equalities, and integer constraints.
New!!: Interior-point method and Feasible region · See more »
Gradient
In mathematics, the gradient is a multi-variable generalization of the derivative.
New!!: Interior-point method and Gradient · See more »
Hessian matrix
In mathematics, the Hessian matrix or Hessian is a square matrix of second-order partial derivatives of a scalar-valued function, or scalar field.
New!!: Interior-point method and Hessian matrix · See more »
Iteration
Iteration is the act of repeating a process, to generate a (possibly unbounded) sequence of outcomes, with the aim of approaching a desired goal, target or result.
New!!: Interior-point method and Iteration · See more »
Jacobian matrix and determinant
In vector calculus, the Jacobian matrix is the matrix of all first-order partial derivatives of a vector-valued function.
New!!: Interior-point method and Jacobian matrix and determinant · See more »
John von Neumann
John von Neumann (Neumann János Lajos,; December 28, 1903 – February 8, 1957) was a Hungarian-American mathematician, physicist, computer scientist, and polymath.
New!!: Interior-point method and John von Neumann · See more »
Karmarkar's algorithm
Karmarkar's algorithm is an algorithm introduced by Narendra Karmarkar in 1984 for solving linear programming problems.
New!!: Interior-point method and Karmarkar's algorithm · See more »
Karush–Kuhn–Tucker conditions
In mathematical optimization, the Karush–Kuhn–Tucker (KKT) conditions, also known as the Kuhn–Tucker conditions, are First-order necessary conditions for a solution in nonlinear programming to be optimal, provided that some regularity conditions are satisfied.
New!!: Interior-point method and Karush–Kuhn–Tucker conditions · See more »
Lagrange multiplier
In mathematical optimization, the method of Lagrange multipliers (named after Joseph-Louis Lagrange) is a strategy for finding the local maxima and minima of a function subject to equality constraints (i.e., subject to the condition that one or more equations have to be satisfied exactly by the chosen values of the variables).
New!!: Interior-point method and Lagrange multiplier · See more »
Leonid Khachiyan
Leonid Genrikhovich Khachiyan (Լեոնիդ Գենրիխովիչ Խաչիյան; Леонид Генрихович Хачиян; May 3, 1952 – April 29, 2005) was a Soviet mathematician of Armenian descent who taught Computer Science at Rutgers University.
New!!: Interior-point method and Leonid Khachiyan · See more »
Linear function
In mathematics, the term linear function refers to two distinct but related notions.
New!!: Interior-point method and Linear function · See more »
Linear programming
Linear programming (LP, also called linear optimization) is a method to achieve the best outcome (such as maximum profit or lowest cost) in a mathematical model whose requirements are represented by linear relationships.
New!!: Interior-point method and Linear programming · See more »
Mehrotra predictor–corrector method
Mehrotra's predictor–corrector method in optimization is a specific interior point method for linear programming.
New!!: Interior-point method and Mehrotra predictor–corrector method · See more »
Narendra Karmarkar
Narendra Krishna Karmarkar (born 1957) is an Indian mathematician, who developed Karmarkar's algorithm.
New!!: Interior-point method and Narendra Karmarkar · See more »
Newton's method
In numerical analysis, Newton's method (also known as the Newton–Raphson method), named after Isaac Newton and Joseph Raphson, is a method for finding successively better approximations to the roots (or zeroes) of a real-valued function.
New!!: Interior-point method and Newton's method · See more »
Nonlinear programming
In mathematics, nonlinear programming is the process of solving an optimization problem defined by a system of equalities and inequalities, collectively termed constraints, over a set of unknown real variables, along with an objective function to be maximized or minimized, where some of the constraints or the objective function are nonlinear.
New!!: Interior-point method and Nonlinear programming · See more »
Penalty method
Penalty methods are a certain class of algorithms for solving constrained optimization problems.
New!!: Interior-point method and Penalty method · See more »
Self-concordant function
In optimization, a self-concordant function is a function f:\mathbb \rightarrow \mathbb for which or, equivalently, a function f:\mathbb \rightarrow \mathbb that, wherever f(x) > 0, satisfies and which satisfies f(x).
New!!: Interior-point method and Self-concordant function · See more »
Sequential quadratic programming
Sequential quadratic programming (SQP) is an iterative method for constrained nonlinear optimization.
New!!: Interior-point method and Sequential quadratic programming · See more »
Simplex algorithm
In mathematical optimization, Dantzig's simplex algorithm (or simplex method) is a popular algorithm for linear programming.
New!!: Interior-point method and Simplex algorithm · See more »
Time complexity
In computer science, the time complexity is the computational complexity that describes the amount of time it takes to run an algorithm.
New!!: Interior-point method and Time complexity · See more »
Yurii Nesterov
Yurii Nesterov is a Russian mathematician, an internationally recognized expert in convex optimization, especially in the development of efficient algorithms and numerical optimization analysis.
New!!: Interior-point method and Yurii Nesterov · See more »
Redirects here:
Barrier method, Barrier method (mathematics), Interior point method, Interior point methods, Interior-point methods, Primal dual method.
References
[1] https://en.wikipedia.org/wiki/Interior-point_method
