Modeling and numerical solution of a cancer therapy optimal control problem
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- A mathematical optimal-control tumor therapy framework consisting of radio- and anti-angiogenesis control strategies that are included in a tumor growth model is investigated. The governing system, resulting from the combination of two well established models, represents the differential constraint of a non-smooth optimal control problem that aims at reducing the volume of the tumor while keeping the radio- and anti-angiogenesis chemical dosage to a minimum. Existence of optimal solutions is proved and necessary conditions are formulated inA mathematical optimal-control tumor therapy framework consisting of radio- and anti-angiogenesis control strategies that are included in a tumor growth model is investigated. The governing system, resulting from the combination of two well established models, represents the differential constraint of a non-smooth optimal control problem that aims at reducing the volume of the tumor while keeping the radio- and anti-angiogenesis chemical dosage to a minimum. Existence of optimal solutions is proved and necessary conditions are formulated in terms of the Pontryagin maximum principle. Based on this principle, a so-called sequential quadratic Hamiltonian (SQH) method is discussed and benchmarked with an “interior point optimizer―a mathematical programming language” (IPOPT-AMPL) algorithm. Results of numerical experiments are presented that successfully validate the SQH solution scheme. Further, it is shown how to choose the optimisation weights in order to obtain treatment functions that successfully reduce the tumor volume to zero.…
Autor(en): | Melina-Lorén Kienle-Garrido, Tim Breitenbach, Kurt Chudej, Alfio Borzì |
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URN: | urn:nbn:de:bvb:20-opus-177152 |
Dokumentart: | Artikel / Aufsatz in einer Zeitschrift |
Institute der Universität: | Fakultät für Mathematik und Informatik / Institut für Mathematik |
Sprache der Veröffentlichung: | Englisch |
Titel des übergeordneten Werkes / der Zeitschrift (Englisch): | Applied Mathematics |
Erscheinungsjahr: | 2018 |
Band / Jahrgang: | 9 |
Heft / Ausgabe: | 8 |
Seitenangabe: | 985-1004 |
Originalveröffentlichung / Quelle: | Applied Mathematics, 2018, 9(8), 985-1004. DOI: 10.4236/am.2018.98067 |
DOI: | https://doi.org/10.4236/am.2018.98067 |
Allgemeine fachliche Zuordnung (DDC-Klassifikation): | 5 Naturwissenschaften und Mathematik / 51 Mathematik / 519 Wahrscheinlichkeiten, angewandte Mathematik |
Freie Schlagwort(e): | cancer; optimal control problem; therapy |
Datum der Freischaltung: | 05.04.2019 |
Sammlungen: | Open-Access-Publikationsfonds / Förderzeitraum 2018 |
Lizenz (Deutsch): | CC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International |