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<!DOCTYPE ArticleSet PUBLIC "-//NLM//DTD PubMed 2.7//EN" "https://dtd.nlm.nih.gov/ncbi/pubmed/in/PubMed.dtd">
<ArticleSet>
<Article>
<Journal>
				<PublisherName>Univrsity of Tehran Press</PublisherName>
				<JournalTitle>Industrial Management Journal</JournalTitle>
				<Issn>3115-7386</Issn>
				<Volume>3</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2011</Year>
					<Month>03</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Using the Fuzzy Models for Ordering System in Inventory Control</ArticleTitle>
<VernacularTitle>استفاده از مدل‌های فازی در سیستم‌های سفارش‌دهی کنترل موجودی</VernacularTitle>
			<FirstPage>99</FirstPage>
			<LastPage>112</LastPage>
			<ELocationID EIdType="pii">22998</ELocationID>
			
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Hassan</FirstName>
					<LastName>Farsijani</LastName>
<Affiliation></Affiliation>

</Author>
<Author>
					<FirstName>Mohammad Reza</FirstName>
					<LastName>Abdoos</LastName>
<Affiliation></Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>1970</Year>
					<Month>01</Month>
					<Day>01</Day>
				</PubDate>
			</History>
		<Abstract>This paper submitting the computation of optimize point of ordering in inventory control systems and particularly for continuous review of ordering system (r,Q) by fuzzy logic method which similarly can be used for other ordering systems. Since in the ordering models we cannot forecast the parameters like cost exactly, we have ambiguity. In this case using precise parameters may cause wrong decision making. In other hand using the statistical methods for parameters like cost is not proper. Therefore in this paper we have provided a method for using fuzzy numbers in the decision making about the ordering systems. For fuzzification we have used trapezoidal fuzzy number and for defuzzification we have used signed distance method. Finally there has been presented a numerical example in order to explain the given model.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">fuzzy model</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Ordering systems</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Signed distance method.</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Trapezoidal fuzzy number</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://imj.ut.ac.ir/article_22998_2d1ead9b8c10a3ece1fb6737e67c39f7.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
