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An Ideal Penalty Function for Constrained Optimization
IMA Journal of Applied Mathematics, 1975This chapter presents an ideal penalty function for constrained optimization. The penalty function is used in the usual way, that is, for any given value of the parameters , S , a vector , ( S ) is obtained that minimizes ϕ( , , S ) without constraints. There is an outer iteration in which and S are changed so as
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Online Function Tracking with Generalized Penalties
2010We attend to the classic setting where an observer needs to inform a tracker about an arbitrary time varying function f: ℕ0 →ℤ. This is an optimization problem, where both wrong values at the tracker and sending updates entail a certain cost. We consider an online variant of this problem, i.e., at time t, the observer only knows f(t′) for all t′≤t.
Marcin Bienkowski, Stefan Schmid 0001
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Penalty function-based method for obtaining a reliability indicator of gravity dam stability
, 2017Yanlong Li +3 more
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An exact penalty function-based differential search algorithm for constrained global optimization
Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2015Jianjun Liu +3 more
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Penalty Function with Memory for Discrete Optimization via Simulation with Stochastic Constraints
Operational Research, 2015Chuljin Park, Seong-Hee Kim
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