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<ArticleSet>
<Article>
<Journal>
				<PublisherName>Payame Noor University (PNU)</PublisherName>
				<JournalTitle>Control and Optimization in Applied Mathematics</JournalTitle>
				<Issn>2383-3130</Issn>
				<Volume>1</Volume>
				<Issue>2</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>10</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>The Control Parametrization Enhancing Technique for Multi-Objective Optimal Control of HIV Dynamic</ArticleTitle>
<VernacularTitle>کنترل بهینه چندهدفه دینامیک ‎HIV‎ به کمک تکنیک پارامتری کردن کنترل</VernacularTitle>
			<FirstPage>1</FirstPage>
			<LastPage>21</LastPage>
			<ELocationID EIdType="pii">3392</ELocationID>
			
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Hassan</FirstName>
					<LastName>Zarei</LastName>
<Affiliation>Department of Mathematic, Payame Noor University, Tehran, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2016</Year>
					<Month>06</Month>
					<Day>27</Day>
				</PubDate>
			</History>
		<Abstract>In this paper‎, ‎a computational approach is adopted for solving a multi-objective optimal control problem (MOOCP) formulation of optimal drug scheduling in human immunodeficiency (HIV) virus infected by individuals‎. ‎The MOOCP‎, ‎which uses a mathematical model of HIV infection‎, ‎has some incompatible objectives‎. ‎The objectives are maximizing the survival time of patients‎, ‎the level of D4‎+ ‎T-cells and the level of cytotoxic T-lymphocytes (CTLs)‎, ‎and minimizing the viral load and the drug costs‎. ‎In this approach the fuzzy goals described by the linear membership functions‎, ‎are incorporated for the objectives and the optimal solution is investigated by maximizing the degree of attainment of the aggregated fuzzy goals resulting a fuzzy goal optimal control problem (FGOCP)‎. ‎Using the minimum operator for aggregation of fuzzy goals‎, ‎the FGOCP is converted into a constrained optimal control problem (OCP) in canonical form‎. ‎The control parametrization enhancing technique (CPET) is used for approximating the OCP by an optimal parameter selection problem‎, ‎with the final goal of implementing continuous and interrupted (structured treatment interruptions‎, ‎STI) combinations of reverse transcriptase inhibitor (RTI) and protease inhibitor (PI) drug efficacies‎. ‎Efficiency of the proposed method is confirmed by numerical simulations.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Multi-objective problem‎</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">‎Optimal control‎</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">‎Fuzzy goal programming‎</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">‎Therapy optimization</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://mathco.journals.pnu.ac.ir/article_3392_b126b5fd552ee258e1bd281c8a5dc268.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
