Results 131 to 140 of about 679,367 (185)
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IFAC Proceedings Volumes, 2000
Abstract Some Optimal Control problems can be reduce to problems of Nonlinear Progran1ming. Methods of penalty functions are widely used in Nonlinear Programming. Theorems of the existence of exact penalty parameters for solving of the problems of Nonlinear Programming by the method of exact penalty functions are proved.
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Abstract Some Optimal Control problems can be reduce to problems of Nonlinear Progran1ming. Methods of penalty functions are widely used in Nonlinear Programming. Theorems of the existence of exact penalty parameters for solving of the problems of Nonlinear Programming by the method of exact penalty functions are proved.
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An M-Objective Penalty Function Algorithm Under Big Penalty Parameters
Journal of Systems Science and Complexity, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zheng, Ying, Meng, Zhiqing, Shen, Rui
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2003
Recall that a relation ≥ defined on a set X is called pre-order if (i) x ≥ x, for all x ∈ X, and (ii) x ≥ y and y ≥ z imply x ≥z. If x ≥ y and y ≥ x, then x and y are called equivalent elements. A pre-order relation is called complete if, for any two elements x and y, either x ≥ y or y ≥ x.
Alexander Rubinov, Xiaoqi Yang
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Recall that a relation ≥ defined on a set X is called pre-order if (i) x ≥ x, for all x ∈ X, and (ii) x ≥ y and y ≥ z imply x ≥z. If x ≥ y and y ≥ x, then x and y are called equivalent elements. A pre-order relation is called complete if, for any two elements x and y, either x ≥ y or y ≥ x.
Alexander Rubinov, Xiaoqi Yang
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Exact Penalty Functions in Constrained Optimization
SIAM Journal on Control and Optimization, 1989Summary: Formal definitions of exactness for penalty functions are introduced and sufficient conditions for a penalty function to be exact according to these definitions are stated, thus providing a unified framework for the study of both nondifferentiale and continuously differentiable penalty functions.
Di Pillo, G., Grippo, L.
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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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