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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>University of Tehran</PublisherName>
				<JournalTitle>Industrial Management Journal</JournalTitle>
				<Issn>2008-5885</Issn>
				<Volume>8</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>04</Month>
					<Day>20</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Designing and selecting the optimal design in terms of risks in new product development</ArticleTitle>
<VernacularTitle>Designing and selecting the optimal design in terms of risks in new product development</VernacularTitle>
			<FirstPage>1</FirstPage>
			<LastPage>22</LastPage>
			<ELocationID EIdType="pii">50694</ELocationID>
			
<ELocationID EIdType="doi">10.22059/imj.2016.50694</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Adel</FirstName>
					<LastName>Azar</LastName>
<Affiliation></Affiliation>
<Identifier Source="ORCID">0000-0003-2123-7579</Identifier>

</Author>
<Author>
					<FirstName>Jafar</FirstName>
					<LastName>Ghaidar Kheljani</LastName>
<Affiliation></Affiliation>
<Identifier Source="ORCID">0000-0002-9382-007X</Identifier>

</Author>
<Author>
					<FirstName>Seyyed Mojtaba</FirstName>
					<LastName>Hashemi Majoumerd</LastName>
<Affiliation></Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2013</Year>
					<Month>12</Month>
					<Day>09</Day>
				</PubDate>
			</History>
		<Abstract>New Product Development (NPD) is one of the key factors for achieving competitive advantage and maintaining firm growth. Therefore, given the importance of this type of projects, this paper is an endeavor to make these projects more successful by effectively managing their risks in the conceptual design phase of new product development. For this purpose, a multi-objective model, with three objective functions, including risk, overall effectiveness of the design and cost, has been developed in this study. Among the innovations and features of this model, one can refer to its considering the mutual effect of risks to the outcomes of one another, as well as its taking into consideration the risks associated with the continuous design variables in calculating the risk measure of product design, which will ultimately lead to an increase in the accuracy of risk measure calculation for each product design.</Abstract>
			<OtherAbstract Language="FA">New Product Development (NPD) is one of the key factors for achieving competitive advantage and maintaining firm growth. Therefore, given the importance of this type of projects, this paper is an endeavor to make these projects more successful by effectively managing their risks in the conceptual design phase of new product development. For this purpose, a multi-objective model, with three objective functions, including risk, overall effectiveness of the design and cost, has been developed in this study. Among the innovations and features of this model, one can refer to its considering the mutual effect of risks to the outcomes of one another, as well as its taking into consideration the risks associated with the continuous design variables in calculating the risk measure of product design, which will ultimately lead to an increase in the accuracy of risk measure calculation for each product design.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">New product development</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">risk</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Effectiveness</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Multi-objective optimization</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">NSGA-II</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://imj.ut.ac.ir/article_50694_1f728556a7a52f7440c457e45d043b08.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>University of Tehran</PublisherName>
				<JournalTitle>Industrial Management Journal</JournalTitle>
				<Issn>2008-5885</Issn>
				<Volume>8</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>04</Month>
					<Day>20</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Prioritizing organization’s quality management projects starting with customer expectations</ArticleTitle>
<VernacularTitle>Prioritizing organization’s quality management projects starting with customer expectations</VernacularTitle>
			<FirstPage>23</FirstPage>
			<LastPage>42</LastPage>
			<ELocationID EIdType="pii">59592</ELocationID>
			
<ELocationID EIdType="doi">10.22059/imj.2016.59592</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Amir</FirstName>
					<LastName>Daneshmand</LastName>
<Affiliation></Affiliation>

</Author>
<Author>
					<FirstName>Shamsodin</FirstName>
					<LastName>Nazemi</LastName>
<Affiliation>Ferdowsi University of Mashhad</Affiliation>

</Author>
<Author>
					<FirstName>Nasser</FirstName>
					<LastName>Motahari</LastName>
<Affiliation>عضو هیئت علمی</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2015</Year>
					<Month>09</Month>
					<Day>21</Day>
				</PubDate>
			</History>
		<Abstract>Customer satisfaction level depends on level that his expectations would be answered. With identifying customer expectations and implementation them in QFD, this ensures that important and critical demands of customer have been considered. QFD have been used and use for translating customer expectations to different subjects. What has been considered in this study, is QFD usage for translating expectation customers to importance mark of quality management projects. Those project that guarantee organization success for meeting customer needs. For this purpose, three matrix approach of QFD was used in “Mashhad urban and suburban railway company” that had concern about ranking of quality management projects. In first matrix, importance marks of technical specifications were identified. In second matrix, importance marks of key operations were identified and in third matrix, execution importance and priority of projects were identified. Study results depicts that “need and task assessment of jobs” has most role in satisfying of customer needs and is first priority for this company.</Abstract>
			<OtherAbstract Language="FA">Customer satisfaction level depends on level that his expectations would be answered. With identifying customer expectations and implementation them in QFD, this ensures that important and critical demands of customer have been considered. QFD have been used and use for translating customer expectations to different subjects. What has been considered in this study, is QFD usage for translating expectation customers to importance mark of quality management projects. Those project that guarantee organization success for meeting customer needs. For this purpose, three matrix approach of QFD was used in “Mashhad urban and suburban railway company” that had concern about ranking of quality management projects. In first matrix, importance marks of technical specifications were identified. In second matrix, importance marks of key operations were identified and in third matrix, execution importance and priority of projects were identified. Study results depicts that “need and task assessment of jobs” has most role in satisfying of customer needs and is first priority for this company.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Quality Management Project</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">quality function deployment</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">QFD</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Urban Transportation</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://imj.ut.ac.ir/article_59592_a8d6ce16a87a587d9db4cc85274a83d2.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>University of Tehran</PublisherName>
				<JournalTitle>Industrial Management Journal</JournalTitle>
				<Issn>2008-5885</Issn>
				<Volume>8</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>04</Month>
					<Day>20</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Analyzing Energy Consumption of Organizational Buildings Using Grey Set Theory</ArticleTitle>
<VernacularTitle>Analyzing Energy Consumption of Organizational Buildings Using Grey Set Theory</VernacularTitle>
			<FirstPage>43</FirstPage>
			<LastPage>60</LastPage>
			<ELocationID EIdType="pii">59595</ELocationID>
			
<ELocationID EIdType="doi">10.22059/imj.2016.59595</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Mostafa</FirstName>
					<LastName>Razavi</LastName>
<Affiliation></Affiliation>

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

</Author>
<Author>
					<FirstName>Hamed</FirstName>
					<LastName>Shakori</LastName>
<Affiliation></Affiliation>

</Author>
<Author>
					<FirstName>Toraj</FirstName>
					<LastName>Karimi</LastName>
<Affiliation></Affiliation>
<Identifier Source="ORCID">0000-0001-0000-10000</Identifier>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2016</Year>
					<Month>03</Month>
					<Day>12</Day>
				</PubDate>
			</History>
		<Abstract>In particular, by identifying clusters of Individuals, households, organizations, cities, countries and nationalities with similar behavioural patterns, it can assist in the crafting of more effective interventions and incentives targeted to specific energy cultures. it also helps energy supply companies understand different behavioural clusters among their customers, so as to better tailor their tariff schemes and products. The purpose of this paper is clustering of buildings by using Grey Set Theory. This theory has the advantage of using fewer data to analyze many factors, and it is therefore more appropriate for this study rather than traditional statistical regression which requires massive data, normal distribution in the data and few variant factors. Gray clustering in this study has been used for two purposes. First, all the variables of building relate to energy audit cluster in two main groups of indicators and the number of variables is reduced. Second, Grey Clustering with Variable Weights has been used to classify all buildings in three categories named “standard”, “Moderate standard deviation” and “completely non-standard”. This classification can be the basis of behavioral research on each group and understanding of cultural differences in each cluster, regardless of technological and structural differences between the buildings. In addition it can be as a tool for understanding the potentials and possibilities for sites of action to achieve behaviour change, whether these are at a general policy level, or targeted at a specific group</Abstract>
			<OtherAbstract Language="FA">In particular, by identifying clusters of Individuals, households, organizations, cities, countries and nationalities with similar behavioural patterns, it can assist in the crafting of more effective interventions and incentives targeted to specific energy cultures. it also helps energy supply companies understand different behavioural clusters among their customers, so as to better tailor their tariff schemes and products. The purpose of this paper is clustering of buildings by using Grey Set Theory. This theory has the advantage of using fewer data to analyze many factors, and it is therefore more appropriate for this study rather than traditional statistical regression which requires massive data, normal distribution in the data and few variant factors. Gray clustering in this study has been used for two purposes. First, all the variables of building relate to energy audit cluster in two main groups of indicators and the number of variables is reduced. Second, Grey Clustering with Variable Weights has been used to classify all buildings in three categories named “standard”, “Moderate standard deviation” and “completely non-standard”. This classification can be the basis of behavioral research on each group and understanding of cultural differences in each cluster, regardless of technological and structural differences between the buildings. In addition it can be as a tool for understanding the potentials and possibilities for sites of action to achieve behaviour change, whether these are at a general policy level, or targeted at a specific group</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Energy audit</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Gray Set Theory</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Grey Clustering</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Iran Oil Ministry</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://imj.ut.ac.ir/article_59595_f463bfd96be71ca9b6f38b9e6b062461.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>University of Tehran</PublisherName>
				<JournalTitle>Industrial Management Journal</JournalTitle>
				<Issn>2008-5885</Issn>
				<Volume>8</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>04</Month>
					<Day>20</Day>
				</PubDate>
			</Journal>
<ArticleTitle>A decision-making model for operational efficiency in the banking workflow process of housing facilities</ArticleTitle>
<VernacularTitle>A decision-making model for operational efficiency in the banking workflow process of housing facilities</VernacularTitle>
			<FirstPage>61</FirstPage>
			<LastPage>74</LastPage>
			<ELocationID EIdType="pii">59598</ELocationID>
			
<ELocationID EIdType="doi">10.22059/imj.2016.59598</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Maryam</FirstName>
					<LastName>Mohammadpanah</LastName>
<Affiliation>Kharazmi University</Affiliation>

</Author>
<Author>
					<FirstName>Reza</FirstName>
					<LastName>Yosefi Zenouz</LastName>
<Affiliation>University of kharazmi</Affiliation>

</Author>
<Author>
					<FirstName>Akbar</FirstName>
					<LastName>Hassanpoor</LastName>
<Affiliation>University of kharazmi</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2015</Year>
					<Month>09</Month>
					<Day>12</Day>
				</PubDate>
			</History>
		<Abstract>Banking and financial services are important parts of the service industry. Quality of service in the banking industry has a close relationship with customer satisfaction service system. Banks could create competitive advantage by increasing customer satisfaction and reduce costs in today&#039;s competitive environment. This paper presents a decision-making model to obtain optimum tasks assignement to personnels in workflow process of housing facilities for the purposes of minimization the average processing time of orders entered into workflow (average time) and also personnel operating costs to minimize banking workflow preocess (operating costs) which it would reduced the waiting times for customers and ultimately higher satisfaction level for the customers. This is a non-linear multi-objective optimization problem and with respect the nature of the variables would be define in a discrete integer space. Since the problems is in NP-hard problems in class, solving the optimization problem has been conducted using non-dominate Sorting Genetic Algorithm II.</Abstract>
			<OtherAbstract Language="FA">Banking and financial services are important parts of the service industry. Quality of service in the banking industry has a close relationship with customer satisfaction service system. Banks could create competitive advantage by increasing customer satisfaction and reduce costs in today&#039;s competitive environment. This paper presents a decision-making model to obtain optimum tasks assignement to personnels in workflow process of housing facilities for the purposes of minimization the average processing time of orders entered into workflow (average time) and also personnel operating costs to minimize banking workflow preocess (operating costs) which it would reduced the waiting times for customers and ultimately higher satisfaction level for the customers. This is a non-linear multi-objective optimization problem and with respect the nature of the variables would be define in a discrete integer space. Since the problems is in NP-hard problems in class, solving the optimization problem has been conducted using non-dominate Sorting Genetic Algorithm II.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">non-dominant Sorting Genetic Algorithm II</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Optimization</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Efficiency</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">workflow bank</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://imj.ut.ac.ir/article_59598_64a7f17cb53f16e9f14ed1688ee30e1f.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>University of Tehran</PublisherName>
				<JournalTitle>Industrial Management Journal</JournalTitle>
				<Issn>2008-5885</Issn>
				<Volume>8</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>04</Month>
					<Day>20</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Solving of vehicle routing problem with cross docking by scatter search algorithm</ArticleTitle>
<VernacularTitle>Solving of vehicle routing problem with cross docking by scatter search algorithm</VernacularTitle>
			<FirstPage>75</FirstPage>
			<LastPage>96</LastPage>
			<ELocationID EIdType="pii">59599</ELocationID>
			
<ELocationID EIdType="doi">10.22059/imj.2016.59599</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Ali</FirstName>
					<LastName>Morovati Sharifabadi</LastName>
<Affiliation></Affiliation>

</Author>
<Author>
					<FirstName>Mahnaz</FirstName>
					<LastName>Bavarkob</LastName>
<Affiliation></Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2014</Year>
					<Month>09</Month>
					<Day>22</Day>
				</PubDate>
			</History>
		<Abstract>One of methods of improvement of the material flow is cross docking that In is considered as a good method to reduce inventory and improve customer satisfaction. Too, the vehicle routing problem is one of the important problems in distribution management and its goal is to find paths for delivering various cargos. Therefore, this study was conducted in order to vehicle routing problem with Cross-docking in MEHRIZ SHADI MEHREGAN Biscuit and the problem was solved with a scatter search Algorithm. The findings concluded that the optimal distance by scatter search Algorithm was equal to 11,438 km that Compared with the current status that improved respectively of 30.54%. The optimal cost by scatter search algorithm was equal to 10186655 that Compared with the current status and improved 6.7%. Therefore, can be concluded that the scatter search Algorithm is a good solution to this problem.</Abstract>
			<OtherAbstract Language="FA">One of methods of improvement of the material flow is cross docking that In is considered as a good method to reduce inventory and improve customer satisfaction. Too, the vehicle routing problem is one of the important problems in distribution management and its goal is to find paths for delivering various cargos. Therefore, this study was conducted in order to vehicle routing problem with Cross-docking in MEHRIZ SHADI MEHREGAN Biscuit and the problem was solved with a scatter search Algorithm. The findings concluded that the optimal distance by scatter search Algorithm was equal to 11,438 km that Compared with the current status that improved respectively of 30.54%. The optimal cost by scatter search algorithm was equal to 10186655 that Compared with the current status and improved 6.7%. Therefore, can be concluded that the scatter search Algorithm is a good solution to this problem.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Supply Chain</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Vehicle routing problem</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">cross docking</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">scatter search algorithm</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://imj.ut.ac.ir/article_59599_f8aa906c24d1301e8c68f3f5f3971412.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>University of Tehran</PublisherName>
				<JournalTitle>Industrial Management Journal</JournalTitle>
				<Issn>2008-5885</Issn>
				<Volume>8</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>04</Month>
					<Day>20</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Estimating warranty costs for the manufacturer and buyer based on a new Pro-Rata Warranty policy</ArticleTitle>
<VernacularTitle>Estimating warranty costs for the manufacturer and buyer based on a new Pro-Rata Warranty policy</VernacularTitle>
			<FirstPage>97</FirstPage>
			<LastPage>112</LastPage>
			<ELocationID EIdType="pii">59601</ELocationID>
			
<ELocationID EIdType="doi">10.22059/imj.2016.59601</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Mahdi</FirstName>
					<LastName>Nasrollahi</LastName>
<Affiliation>Faculty member of the International University of Imam Khomeini</Affiliation>

</Author>
<Author>
					<FirstName>Ezzatollah</FirstName>
					<LastName>Asgharizadeh</LastName>
<Affiliation>Associate Professor of Industrial Management University of Tehran</Affiliation>
<Identifier Source="ORCID">0000-0001-7048-9065</Identifier>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2015</Year>
					<Month>11</Month>
					<Day>17</Day>
				</PubDate>
			</History>
		<Abstract>Currently, a large number of products are being sold with warranty policies. Pro-rata warranties are relatively a complex concept. This paper focuses on developing a new Pro-rata warranty policy. In this model components of the product are grouped into two disjointed sets, failures of components belonging to set one are covered by PRW warranty and those components that belonging to set two are not covered under warranty. In order to design the new policy, two different approaches were designed that in any approach the product failure rates are estimated separately. The proposed model helps manufacturer to have a precise estimate of the expected costs and determine the warranty price based on this estimation. As a result of reduction of expected warranty costs and consequently the price, the customer will also benefit. Finally, the sensitivity of warranty model is analyzed with a numerical example.</Abstract>
			<OtherAbstract Language="FA">Currently, a large number of products are being sold with warranty policies. Pro-rata warranties are relatively a complex concept. This paper focuses on developing a new Pro-rata warranty policy. In this model components of the product are grouped into two disjointed sets, failures of components belonging to set one are covered by PRW warranty and those components that belonging to set two are not covered under warranty. In order to design the new policy, two different approaches were designed that in any approach the product failure rates are estimated separately. The proposed model helps manufacturer to have a precise estimate of the expected costs and determine the warranty price based on this estimation. As a result of reduction of expected warranty costs and consequently the price, the customer will also benefit. Finally, the sensitivity of warranty model is analyzed with a numerical example.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Pro-Rata Warranty</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Warranty</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Warranty cost</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Warranty policies</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://imj.ut.ac.ir/article_59601_37a83eb9f6d428aa4f90249c27a8cdc2.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>University of Tehran</PublisherName>
				<JournalTitle>Industrial Management Journal</JournalTitle>
				<Issn>2008-5885</Issn>
				<Volume>8</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2016</Year>
					<Month>04</Month>
					<Day>20</Day>
				</PubDate>
			</Journal>
<ArticleTitle>An Inventory–Scheduling Model for Supply Chain of Construction Project</ArticleTitle>
<VernacularTitle>An Inventory–Scheduling Model for Supply Chain of Construction Project</VernacularTitle>
			<FirstPage>113</FirstPage>
			<LastPage>140</LastPage>
			<ELocationID EIdType="pii">59602</ELocationID>
			
<ELocationID EIdType="doi">10.22059/imj.2016.59602</ELocationID>
			
			<Language>FA</Language>
<AuthorList>
<Author>
					<FirstName>Mohammad Reza</FirstName>
					<LastName>Vakili</LastName>
<Affiliation></Affiliation>

</Author>
<Author>
					<FirstName>Siamk</FirstName>
					<LastName>Nori</LastName>
<Affiliation></Affiliation>

</Author>
<Author>
					<FirstName>Sseid</FirstName>
					<LastName>Yaghobi</LastName>
<Affiliation>عضو هیئت علمی</Affiliation>
<Identifier Source="ORCID">0000-0003-1218-9050</Identifier>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2015</Year>
					<Month>09</Month>
					<Day>16</Day>
				</PubDate>
			</History>
		<Abstract>One of the important problems in project management is lack of available resources in proper time at project site that leads to lack of project implementation in due date. This problem may be lead to time delay in sending resources from suppliers and related origins in supply chain to project site. Therfore, to better resources managmenet and also the improvement of supply chain condition, the time delay problem in resources supply can be solved by determining the optimal quantity of order in supply chain based on project constraints and required time for implementation of supply chain activities. Accordingly, in this paper a mamathemical model is proposed for determining the optimal quantity of orders and activities duration of supply chain, in which the total holding cost in project site and also supply chain cost are minimized. The mentioned model is first linearized and then by using the numerical examples, the results analyziz are presented.</Abstract>
			<OtherAbstract Language="FA">One of the important problems in project management is lack of available resources in proper time at project site that leads to lack of project implementation in due date. This problem may be lead to time delay in sending resources from suppliers and related origins in supply chain to project site. Therfore, to better resources managmenet and also the improvement of supply chain condition, the time delay problem in resources supply can be solved by determining the optimal quantity of order in supply chain based on project constraints and required time for implementation of supply chain activities. Accordingly, in this paper a mamathemical model is proposed for determining the optimal quantity of orders and activities duration of supply chain, in which the total holding cost in project site and also supply chain cost are minimized. The mentioned model is first linearized and then by using the numerical examples, the results analyziz are presented.</OtherAbstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Construction Supply Chain</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Duration of Supply Chain's Activities</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Optimal Quantity of Order</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Mathematical model</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://imj.ut.ac.ir/article_59602_4b417737383d647bbc31ae114d2ca7e2.pdf</ArchiveCopySource>
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