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<ArticleSet>
<Article>
<Journal>
				<PublisherName>Morvarid Derakhshan Andisheh</PublisherName>
				<JournalTitle>Journal of Quality Engineering and Management</JournalTitle>
				<Issn>3134-0849</Issn>
				<Volume>11</Volume>
				<Issue>4</Issue>
				<PubDate PubStatus="epublish">
					<Year>2022</Year>
					<Month>02</Month>
					<Day>20</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Mathematical modeling of resource allocation in critical conditions with the aim of increasing the level of resilience of operational processes: the case study of the textile industry</ArticleTitle>
<VernacularTitle>Mathematical modeling of resource allocation in critical conditions with the aim of increasing the level of resilience of operational processes: the case study of the textile industry</VernacularTitle>
			<FirstPage>393</FirstPage>
			<LastPage>412</LastPage>
			<ELocationID EIdType="pii">159884</ELocationID>
			
<ELocationID EIdType="doi">10.48313/jqem.2022.159884</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Mahnaz</FirstName>
					<LastName>Ebrahimi-Sadrabadi</LastName>
<Affiliation>Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Ali</FirstName>
					<LastName>Husseinzadeh Kashan</LastName>
<Affiliation>Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran</Affiliation>
<Identifier Source="ORCID">0000-0002-6004-6882</Identifier>

</Author>
<Author>
					<FirstName>Mohammad Mehdi</FirstName>
					<LastName>Sepehri</LastName>
<Affiliation>Faculty of Industrial and Systems Engineering, Tarbiat Modares University, Tehran, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2022</Year>
					<Month>05</Month>
					<Day>26</Day>
				</PubDate>
			</History>
		<Abstract>As time goes on and crises increase in societies, organizations are increasingly exposed to disruption. These crises can be of natural (such as earthquakes, floods, and fires) or human (such as terrorist attacks, infectious diseases, and intentional or inadvertent employee errors). Therefore, organizations need to be resilient to protect themselves from harmful consequences. The basic aspect of resilience involves the ability of an element to return to normal after disruption and resource allocation. Obviously, in any organization, the primary goal is to allocate the least resources to recover operations and to bring activities back to the tolerance threshold so that destructive events do not stop vital activities. In this paper, a quantitative model for resource allocation is presented, which minimizes the lack of resilience. The problem has a basic assumption, that there is a shortage of resources in at least one of the available resources due to excessive demand. After solving the model by numerical experiment, the results of the model were described and it was found that destructive events were retrieved before the tolerance threshold.</Abstract>
			<OtherAbstract Language="FA">As time goes on and crises increase in societies, organizations are increasingly exposed to disruption. These crises can be of natural (such as earthquakes, floods, and fires) or human (such as terrorist attacks, infectious diseases, and intentional or inadvertent employee errors). Therefore, organizations need to be resilient to protect themselves from harmful consequences. The basic aspect of resilience involves the ability of an element to return to normal after disruption and resource allocation. Obviously, in any organization, the primary goal is to allocate the least resources to recover operations and to bring activities back to the tolerance threshold so that destructive events do not stop vital activities. In this paper, a quantitative model for resource allocation is presented, which minimizes the lack of resilience. The problem has a basic assumption, that there is a shortage of resources in at least one of the available resources due to excessive demand. After solving the model by numerical experiment, the results of the model were described and it was found that destructive events were retrieved before the tolerance threshold.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Process Optimization</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Process resilience</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Resource Allocation</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Lack of resources</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://www.pqprc.ir/article_159884_817499e33d049ab49fd00ce91122250b.pdf</ArchiveCopySource>
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