Robust penalty function method for an uncertain multi-time control optimization problems

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URI: http://hdl.handle.net/10498/40417
DOI: https://doi.org/10.1016/j.jmaa.2021.125453
ISSN: 1096-0813
ISSN: 0022-247X
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2022-01-01Department
Estadística e Investigación OperativaSource
Journal of Mathematical Analysis and Applications - 2022, Vol. 505, n. 1, 125453Abstract
This paper gives some new results on multi-time first-order PDE constrained control optimization problem in the face of data uncertainty (MCOPU). We obtain the robust sufficient optimality conditions for (MCOPU). Further, we construct an unconstrained multi-time control optimization problem (MCOPU) corresponding to (MCOPU) via absolute value penalty function method. Then, we show that the robust optimal solution to the constrained problem and a robust minimizer to the unconstrained problem are equivalent under suitable hypotheses. Moreover, we give some non-trivial examples to validate the results established in this paper
Subjects
Absolute value penalty function method; Convexity Multi-time control optimization problem; Robust necessary optimality conditions; Robust optimal solutionCollections
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- Articulos Científicos Est. I.O. [360]





