Multiobjective Optimal Control of HIV Dynamics

Various aspects of the interaction of HIV with the human immune system can be modeled by a system of ordinary differential equations. This model is utilized, and a multiobjective optimal control problem (MOOCP) is proposed to maximize the CD4+ T cells population and minimize both the viral load and...

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Vydáno v:Mathematical Problems in Engineering Ročník 2010; číslo 1; s. 532 - 560-134
Hlavní autoři: Zarei, Hassan, Kamyad, Ali Vahidian, Effati, Sohrab
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Hindawi Limiteds 01.01.2010
Hindawi Publishing Corporation
John Wiley & Sons, Inc
Témata:
Antiretroviral drugs
Control systems
Differential equations
Drug resistance
HIV
Human immunodeficiency virus
Immune system
Linear programming
Lymphocytes
Mathematical models
Mathematical problems
Multiple objective analysis
Optimal control
Optimization
Pareto optimum
Predictive control
Protease inhibitors
Studies
ISSN:1024-123X, 1563-5147
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Shrnutí:Various aspects of the interaction of HIV with the human immune system can be modeled by a system of ordinary differential equations. This model is utilized, and a multiobjective optimal control problem (MOOCP) is proposed to maximize the CD4+ T cells population and minimize both the viral load and drug costs. The weighted sum method is used, and continuous Pareto optimal solutions are derived by solving the corresponding optimality system. Moreover, a model predictive control (MPC) strategy is applied, with the final goal of implementing Pareto optimal structured treatment interruptions (STI) protocol. In particular, by using a fuzzy approach, the MOOCP is converted to a single-objective optimization problem to derive a Pareto optimal solution which among other Pareto optimal solutions has the best satisfaction performance. Then, by using an embedding method, the problem is transferred into a modified problem in an appropriate space in which the existence of solution is guaranteed by compactness of the space. The metamorphosed problem is approximated by a linear programming (LP) model, and a piecewise constant solution which shows the desired combinations of reverse transcriptase inhibitor (RTI) and protease inhibitor (PI) drug efficacies is achieved.
Bibliografie:ObjectType-Article-1
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ISSN:1024-123X
1563-5147
DOI:10.1155/2010/568315