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English-russian dictionary of physics. 2013.
Lagrange constraint
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Lagrange multiplier — Figure 1: Find x and y to maximize f(x,y) subject to a constraint (shown in red) g(x,y) = c … Wikipedia
Lagrange multipliers — In mathematical optimization problems, the method of Lagrange multipliers, named after Joseph Louis Lagrange, is a method for finding the extrema of a function of several variables subject to one or more constraints; it is the basic tool in… … Wikipedia
Constraint algorithm — In mechanics, a constraint algorithm is a method for satisfying constraints for bodies that obey Newton s equations of motion. There are three basic approaches to satisfying such constraints: choosing novel unconstrained coordinates ( internal… … Wikipedia
Lagrange multipliers on Banach spaces — In the field of calculus of variations in mathematics, the method of Lagrange multipliers on Banach spaces can be used to solve certain infinite dimensional constrained optimization problems. The method is a generalization of the classical method … Wikipedia
Constraint optimization — In constraint satisfaction, constrained optimization (also called constraint optimization) seeks for a solution maximizing or minimizing a cost function. Contents 1 Definition 2 Solution methods 2.1 Branch and bound … Wikipedia
Constraint (mathematics) — In mathematics, a constraint is a condition that a solution to an optimization problem must satisfy. There are two types of constraints: equality constraints and inequality constraints. The set of solutions that satisfy all constraints is called… … Wikipedia
Constrained optimization and Lagrange multipliers — This tutorial presents an introduction to optimization problems that involve finding a maximum or a minimum value of an objective function f(x 1,x 2,ldots, x n) subject to a constraint of the form g(x 1,x 2,ldots, x n)=k.Maximum and… … Wikipedia
Multibody system — A multibody system is used to model the dynamic behavior of interconnected rigid or flexible bodies, each of which may undergo large translational and rotational displacements. Contents 1 Introduction 2 Applications 3 Example 4 Concept … Wikipedia
Kkt — Die Konvexe Optimierung ist ein Teilgebiet der mathematischen Optimierung. Es ist eine bestimmte Größe zu minimieren, die sogenannte Zielfunktion, welche von einem Parameter, welcher mit x bezeichnet wird, abhängt. Außerdem sind bestimmte… … Deutsch Wikipedia
Kuhn-Tucker-Bedingungen — Die Konvexe Optimierung ist ein Teilgebiet der mathematischen Optimierung. Es ist eine bestimmte Größe zu minimieren, die sogenannte Zielfunktion, welche von einem Parameter, welcher mit x bezeichnet wird, abhängt. Außerdem sind bestimmte… … Deutsch Wikipedia
Second class constraints — In a constrained Hamiltonian system, a dynamical quantity is second class if its Poisson bracket with at least one constraint is nonvanishing. A constraint that has a nonzero Poisson bracket with at least one other constraint, then, is a second… … Wikipedia
