nonlinear+programming

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• Nonlinear programming — In mathematics, nonlinear programming (NLP) is the process of solving 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,… …   Wikipedia

• nonlinear programming — netiesinis programavimas statusas T sritis automatika atitikmenys: angl. nonlinear programming vok. nichtlineare Programmierung, f rus. нелинейное программирование, n pranc. programmation non linéaire, f …   Automatikos terminų žodynas

• Nonlinear conjugate gradient method — In numerical optimization, the nonlinear conjugate gradient method generalizes the conjugate gradient method to nonlinear optimization. For a quadratic function : The minimum of f is obtained when the gradient is 0: . Whereas linear conjugate… …   Wikipedia

• Nonlinear dimensionality reduction — High dimensional data, meaning data that requires more than two or three dimensions to represent, can be difficult to interpret. One approach to simplification is to assume that the data of interest lies on an embedded non linear manifold within… …   Wikipedia

• Nonlinear gameplay — See also: Open world A video game with nonlinear gameplay presents players with challenges that can be completed in a number of different sequences. Each player sees only some of the challenges possible, and the same challenges may be played in a …   Wikipedia

• Nonlinear complementarity problem — In applied mathematics, a nonlinear complementarity problem (NCP) with respect to a mapping ƒ : Rn → Rn, denoted by NCPƒ, is to find a vector x ∈ Rn such that where ƒ(x) is a smooth mapping. References Stephen C.… …   Wikipedia

• Linear programming — (LP, or linear optimization) is a mathematical method for determining a way to achieve the best outcome (such as maximum profit or lowest cost) in a given mathematical model for some list of requirements represented as linear relationships.… …   Wikipedia

• mathematical programming — Application of mathematical and computer programming techniques to the construction of deterministic models, principally for business and economics. For models that only require linear algebraic equations, the techniques are called linear… …   Universalium

• Sequential quadratic programming — (SQP) is one of the most popular and robust algorithms for nonlinear continuous optimization. The method is based on solving a series of subproblems designed to minimize a quadratic model of the objective subject to a linearization of the… …   Wikipedia

• Semidefinite programming — (SDP) is a subfield of convex optimization concerned with the optimization of a linear objective function over the intersection of the cone of positive semidefinite matrices with an affine space.Semidefinite programming is a relatively new field… …   Wikipedia

• Dynamic programming — For the programming paradigm, see Dynamic programming language. In mathematics and computer science, dynamic programming is a method for solving complex problems by breaking them down into simpler subproblems. It is applicable to problems… …   Wikipedia