The Dubovitskii and Milyutin Methodology Applied to an Optimal Control Problem Originating in an Ecological System
Abstract
1. Introduction
2. Assumptions and Statements of Main Results
2.1. Assumptions
2.2. Statements of Main Results
- (a)
- The sets
- (b)
- The application M is Gâteaux differentiable and the derivative of M in is defined by if and only if
- (c)
- The application M is strictly differentiable and is a surjective operator.
- (d)
- The following sets
3. Preliminaries
4. Proofs of Main Results
4.1. Proof of Theorem 1
- Step 1:
- Local solutions via a truncated problem. Let us consider the truncated Cauchy problem
- Step 2:
- The local solution is a global solution. To prove that the local solution on is a global solution it suffices to prove that is bounded on . Indeed, from (2c), the positivity of on deduced on Step 1 together with the positivity of g on given by Assumption 4, the strictly positivity of assumed in Assumption 2, and the fact that and is strictly positive on Ω (considered on Assumption 3), we deduce that for . Then, .
- Step 3:
4.2. Proof of Lemma 1
4.3. Proof of Theorem 2
5. Conclusions and Future Work
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Conflicts of Interest
References
- Cantrell, R.S.; Cosner, C. Spatial Ecology via Reaction—Diffusion Equations; Wiley Series in Mathematical and Computational Biology; John Wiley & Sons, Ltd.: Chichester, UK, 2003. [Google Scholar]
- El Khatib, N.; Kafi, O.; Sequeira, A.; Simakov, S.; Vassilevski, Y.; Volpert, V. Mathematical modelling of atherosclerosis. Math. Model. Nat. Phenom. 2019, 14, 25. [Google Scholar] [CrossRef]
- Murray, J.D. Mathematical Biology. I. An introduction. In Interdisciplinary Applied Mathematics, 17, 3rd ed.; Springer: New York, NY, USA, 2002. [Google Scholar]
- Murray, J.D. Mathematical biology. II. Spatial models and biomedical applications. In Interdisciplinary Applied Mathematics, 18, 3rd ed.; Springer: New York, NY, USA, 2003. [Google Scholar]
- Panfilov, A.V.; Dierckx, H.; Volpert, V. Reaction-diffusion waves in cardiovascular diseases. Phys. D 2019, 399, 1–34. [Google Scholar] [CrossRef]
- Xiang, H.; Liu, B.; Fang, Z. Optimal control strategies for a new ecosystem governed by reaction–diffusion equations. J. Math. Anal. Appl. 2018, 467, 270–291. [Google Scholar] [CrossRef]
- Evans, L.C. Partial Differential Equations; American Mathematical Society: Providence, RI, USA, 1997. [Google Scholar]
- Apreutesei, N.C. Necessary optimality conditions for a Lotka—Volterra three species system. Math. Model. Nat. Phenom. 2006, 1, 123–135. [Google Scholar] [CrossRef][Green Version]
- Apreutesei, N.C. An optimal control problem for prey—Predator system with a general functional response. Appl. Math. Lett. 2009, 22, 1062–1065. [Google Scholar] [CrossRef]
- Apreutesei, N.C. An optimal control problem for pest, predator, and plant system. Nonlinear Anal. Real World Appl. 2012, 13, 1391–1400. [Google Scholar] [CrossRef]
- Apreutesei, N.; Dimitriu, G.; Strugariu, R. An optimal control problem for a two–prey and one—Predator model with diffusion. Comput. Math. Appl. 2014, 67, 2127–2143. [Google Scholar] [CrossRef]
- Arnautu, V.; Barbu, V.; Capasso, V. Controlling the spread of epidemics. Appl. Math. Optim. 1989, 20, 297–317. [Google Scholar] [CrossRef]
- Coronel, A.; Guillén-González, F.; Marques-Lopes, F.; Rojas-Medar, M. The Dubovitskii and Milyutin Formalism Applied to an Optimal Control Problem in a Solidification Model. In Recent Advances in PDEs: Analysis, Numerics and Control; Doubova, A., González-Burgos, M., Guillén-González, F., Marín Beltrán, M., Eds.; SEMA SIMAI Springer Series; Springer: Cham, Switzerland, 2018; Volume 17. [Google Scholar]
- Coronel, A.; Huancas, F.; Sepúlveda, M. Identification of space distributed coefficients in an indirectly transmitted diseases model. Inverse Probl. 2019, 35, 115001. [Google Scholar] [CrossRef]
- Coronel, A.; Huancas, F.; Sepúlveda, M. A note on the existence and stability of an inverse problem for a SIS model. Comput. Math. Appl. 2019, 77, 3186–3194. [Google Scholar] [CrossRef]
- Dai, F.; Liu, B. Optimal control problem for a general reaction-diffusion eco-epidemiological model with disease in prey. Appl. Math. Model. 2020, 88, 1–20. [Google Scholar] [CrossRef]
- Dai, F.; Liu, B. Optimal control problem for a general reaction-diffusion tumor-immune system with chemotherapy. J. Frankl. Inst. 2021, 358, 448–473. [Google Scholar] [CrossRef]
- Filliger, R.; Hongler, M.-O.; Streit, L. Connection between an exactly solvable stochastic optimal control problem and a nonlinear reaction-diffusion equation. J. Optim. Theory Appl. 2008, 137, 497–505. [Google Scholar] [CrossRef]
- Fu, H.; Guo, H.; Hou, J.; Zhao, J. A priori error analysis of stabilized mixed finite element method for reaction-diffusion optimal control problems. Bound. Value Probl. 2016, 2016, 1–20. [Google Scholar] [CrossRef]
- Garvie, M.R.; Trenchea, C. Optimal control of a nutrient-phytoplankton-zooplankton-fish system. SIAM J. Control Optim. 2007, 46, 775–791. [Google Scholar] [CrossRef]
- Gayte, I.; Guillén-González, F.; Rojas-Medar, M. Dubovitskii-Milyutin formalism applied to optimal control problems with constraints given by the heat equation with final data. IMA J. Math. Control Inform. 2010, 27, 57–76. [Google Scholar] [CrossRef]
- Huili, X.; Bin, L. Solving the inverse problem of an SIS epidemic reaction—Diffusion model by optimal control methods. Comput. Math. Appl. 2015, 70, 805–819. [Google Scholar]
- Jang, J.; Kwon, H.-D.; Lee, J. Optimal control problem of an SIR reaction-diffusion model with inequality constraints. Math. Comput. Simul. 2020, 171, 136–151. [Google Scholar] [CrossRef]
- Jau, G.-C. The problem of the nonlinear diffusive predator-prey model with the same biotic resource. Nonlinear Anal. Real World Appl. 2017, 34, 188–200. [Google Scholar] [CrossRef]
- Shangerganesh, L.; Sowndarrajan, P.T. Optimal control problem for cancer invasion reaction-diffusion system. Numer. Funct. Anal. Optim. 2018, 39, 1574–1593. [Google Scholar] [CrossRef]
- Tröltzsch, F. Optimal control of partial differential equations. Theory, methods and applications. In Graduate Studies in Mathematics, 112; American Mathematical Society: Providence, RI, USA, 2010. [Google Scholar]
- Wang, F.; Zhang, Z.; Zhou, Z. A spectral Galerkin approximation of optimal control problem governed by fractional advection-diffusion-reaction equations. J. Comput. Appl. Math. 2021, 386, 113233. [Google Scholar] [CrossRef]
- Zhang, L.; Liu, B. Optimal control problem for an ecosystem with two competing preys and one predator. J. Math. Anal. Appl. 2015, 424, 201–220. [Google Scholar] [CrossRef]
- Brezis, H. Analyse Fonctionnelle: Theórie et Applications; Masson, (Collection Mathématiques Appliqués Pour la Maitrise); Dunod: Paris, France, 1987. [Google Scholar]
- Girsanov, I.V. Lectures Notes in Economics and Mathematical Systems; Springer: Berlin, Germany; New York, NY, USA, 1972; Volume 67. [Google Scholar]
- Kotarski, W. Characterization of Pareto Optimal Points in Problems with Multi-Equality Constraints. Optimization 1989, 20, 93–106. [Google Scholar] [CrossRef]
- Jahn, J. Introduction to the Theory of Nonlinear Optimization; Springer: Berlin, Germany, 1994. [Google Scholar]
- Tröltzsch, F.; Wachsmuth, D. On the switching behavior of sparse optimal controls for the one-dimensional heat equation. Math. Control Relat. Fields 2018, 8, 135–153. [Google Scholar]
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Coronel, A.; Huancas, F.; Lozada, E.; Rojas-Medar, M. The Dubovitskii and Milyutin Methodology Applied to an Optimal Control Problem Originating in an Ecological System. Mathematics 2021, 9, 479. https://doi.org/10.3390/math9050479
Coronel A, Huancas F, Lozada E, Rojas-Medar M. The Dubovitskii and Milyutin Methodology Applied to an Optimal Control Problem Originating in an Ecological System. Mathematics. 2021; 9(5):479. https://doi.org/10.3390/math9050479
Chicago/Turabian StyleCoronel, Aníbal, Fernando Huancas, Esperanza Lozada, and Marko Rojas-Medar. 2021. "The Dubovitskii and Milyutin Methodology Applied to an Optimal Control Problem Originating in an Ecological System" Mathematics 9, no. 5: 479. https://doi.org/10.3390/math9050479
APA StyleCoronel, A., Huancas, F., Lozada, E., & Rojas-Medar, M. (2021). The Dubovitskii and Milyutin Methodology Applied to an Optimal Control Problem Originating in an Ecological System. Mathematics, 9(5), 479. https://doi.org/10.3390/math9050479