Results 251 to 260 of about 8,190 (293)
Norm Penalized Joint-Optimization NLMS Algorithms for Broadband Sparse Adaptive Channel Estimation [PDF]
Symmetry, 2017 A joint-optimization method is proposed for enhancing the behavior of the l 1 -norm- and sum-log norm-penalized NLMS algorithms to meet the requirements of sparse adaptive channel estimations.
Yanyan Wang, Yingsong Li, Li Yingsong
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Integer optimization with penalized fractional values: The Knapsack case [PDF]
European Journal of Operational Research, 2019 We consider integer optimization problems where variables can potentially take fractional values, but this occurrence is penalized in the objective function. This general situation has relevant examples in scheduling (preemption), routing (split delivery)
Enrico Malaguti +2 more
exaly +3 more sources
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An optimal design problem with perimeter penalization
Calculus of Variations and Partial Differential Equations, 1993zbMATH Open Web Interface contents unavailable due to conflicting licenses.
AMBROSIO, Luigi, Buttazzo G.
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On the Penalization Approach to Optimal Control Problems
IFAC Proceedings Volumes, 2000Abstract The Exact Penalization Technique is applied to treat optimal control problems in a system described by ordinary differential equations. The resulting functional is essentially nonsmooth but directionally differentiable (even subdifferentiable). Differential equations are viewed as constraints and are “removed” by introducing an exact penalty
Vladimir F. Demyanov +2 more
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Optimal Control Applications and Methods, 2022
AbstractThe purpose of this article is twofold. We first develop the first‐order necessary optimality conditions for a general constrained fractional optimal control problem using calculus of variation. These conditions are of the form of fractional ordinary differential equations which reduce to the conventional Euler–Lagrange equations when the ...
Song Wang, Wen Li, Chongyang Liu
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AbstractThe purpose of this article is twofold. We first develop the first‐order necessary optimality conditions for a general constrained fractional optimal control problem using calculus of variation. These conditions are of the form of fractional ordinary differential equations which reduce to the conventional Euler–Lagrange equations when the ...
Song Wang, Wen Li, Chongyang Liu
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Penalization techniques in L ∞ optimization problems with unbounded horizon
Annals of Operations Research, 2007zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Laura S. Aragone +2 more
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Optimal Control Problems and Penalization
2000The Exact Penalization Technique is applied to treat optimal control problems in a system described by ordinary differential equations. The resulting functional is essentially nonsmooth but directionally differentiable (even subdifferentiable). Differential equations are viewed as constraints and are “removed” by introducing an exact penalty function ...
Vladimir F. Demyanov +2 more
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Exact Penalizations for Optimal Control Problems
IEEE Transactions on Automatic ControlA novel technique to solve optimal control problems with state constraints is proposed. We exploit the theory of exact penalty functions, used in mathematical programming, to construct a systematic procedure to transform two classes of problems with state constraints to equivalent penalized unconstrained problems. We focus on a special class of systems
Riccardo A. Grimaldi, Alessandro Astolfi
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A modified local quadratic approximation algorithm for penalized optimization problems
Computational Statistics & Data Analysis, 2016zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Sangin Lee, Sunghoon Kwon, Yongdai Kim
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Exact Penalization and Necessary Optimality Conditions for Generalized Bilevel Programming Problems
SIAM Journal on Optimization, 1997Summary: The generalized bilevel programming problem (GBLP) is a bilevel mathematical program where the lower level is a variational inequality. In this paper we prove that if the objective function of a GBLP is uniformly Lipschitz continuous in the lower level decision variable with respect to the upper level decision variable, then using certain ...
Jane J. Ye, Daoli Zhu, Qiji Jim Zhu
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