A measure space approach to optimal source placement
AbstractThe problem of optimal placement of point sources is formulated as a distributed optimal control problem with sparsity constraints. For practical relevance, partial observations as well as partial and non-negative controls need to be considered. Although well-posedness of this problem requires a non-reflexive Banach space setting, a primal-predual formulation of the optimality system can be approximated well by a family of semi-smooth equations, which can be solved by a superlinearly convergent semi-smooth Newton method. Numerical examples indicate the feasibility for optimal light source placement problems in diffusive photochemotherapy. Copyright Springer Science+Business Media, LLC 2012
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Bibliographic InfoArticle provided by Springer in its journal Computational Optimization and Applications.
Volume (Year): 53 (2012)
Issue (Month): 1 (September)
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Web page: http://www.springer.com/math/journal/10589
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- Michael Hintermüller & Tao Wu, 2014. "A superlinearly convergent R-regularized Newton scheme for variational models with concave sparsity-promoting priors," Computational Optimization and Applications, Springer, vol. 57(1), pages 1-25, January.
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