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Second-Order Analysis of Penalty Function
Journal of Optimization Theory and Applications, 2010The authors study global exact penalty properties for general nonlinear programming problems. Global exact penalty properties are conditions under which every global minimum of the original problem is also a global minimum of the penalized problem. The global second-order sufficient conditions are similar to those in [\textit{X. Q. Yang}, Math. Program.
Yang, X. Q., Zhou, Y. Y.
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1992
Since the early 1970s, some estimation-type identification procedures have been proposed. They are to choose the orders k and i minimizing $$P(k,i) = {\text{ln}}{\overset{\lower0.5em\hbox{$\smash{\scriptscriptstyle\smile}$}}{\sigma }}\mathop{{k,i}}\limits^{2} + (k + i)\frac{{C(T)}}{T}$$ , where σ k,i 2 is an estimate of the white noise variance ...
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Since the early 1970s, some estimation-type identification procedures have been proposed. They are to choose the orders k and i minimizing $$P(k,i) = {\text{ln}}{\overset{\lower0.5em\hbox{$\smash{\scriptscriptstyle\smile}$}}{\sigma }}\mathop{{k,i}}\limits^{2} + (k + i)\frac{{C(T)}}{T}$$ , where σ k,i 2 is an estimate of the white noise variance ...
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Nonlinear programming without a penalty function
Mathematical Programming, 2002zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fletcher, Roger, Leyffer, Sven
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Penalty function techniques: A tutorial
Computers & Industrial Engineering, 1985Abstract This tutorial surveys several unconstrained methods for solving constrained mathematical programming problems. The paper presents a historical development of the transformation approach in order to give a general sense for the appropriateness of these methodologies.
Bruce R. Feiring +2 more
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Stochastic penalty function optimization
1973 IEEE Conference on Decision and Control including the 12th Symposium on Adaptive Processes, 1973We investigate a stochastic penalty algorithm, which can be used to find a constrained optimum point for a concave or convex objective function subject to a nonlinear constraint which forms a connected region, even when we do not have the objective function available, but only have a noisy estimate of the objective function.
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A New Multiplier Penalty Functions
2010 International Conference on E-Product E-Service and E-Entertainment, 2010In this paper, the author converts inequality constrained optimization problem into equality constrained optimization problem by using slack variables. Then we construct a new multiplier penalty function using the penalty function who belongs to equality constraints and was raised by Bertskas in 1982.
Yanli Han, Shujie Jing
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The Generalized Penalty-Function/Surrogate Model
Operations Research, 1973This paper combines the monotonic-penalty-function and surrogate models into a general model called the penalty-function/surrogate model. It unifies and generalizes the central theorems of earlier papers, and provides some new theorems that can be specialized to the Lagrangian penalty-function model (GLM) or to linear surrogates.
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On differentiable exact penalty functions
Journal of Optimization Theory and Applications, 1986We study a differentiable exact penalty function for solving twice continuously differentiable inequality constrained optimization problems. Under certain assumptions on the parameters of the penalty function, we show the equivalence of the stationary points of this function and the Kuhn-Tucker points of the restricted problem as well as their extreme ...
Vinante, C., Pintos, S.
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Penalty function versus non-penalty function methods for constrained nonlinear programming problems
Mathematical Programming, 1971The relative merits of using sequential unconstrained methods for solving: minimizef(x) subject togi(x) ź 0, i = 1, ź, m, hj(x) = 0, j = 1, ź, p versus methods which handle the constraints directly are explored. Nonlinearly constrained problems are emphasized.
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Penalty Functions in a Control Problem
Automation and Remote Control, 2004zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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