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<Article>
<Journal>
				<PublisherName>Kharazmi University</PublisherName>
				<JournalTitle>International Journal of Supply and Operations Management</JournalTitle>
				<Issn>2383-1359</Issn>
				<Volume>2</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2015</Year>
					<Month>05</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>An EPQ Model with Increasing Demand and Demand Dependent Production Rate under Trade Credit Financing</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>532</FirstPage>
			<LastPage>547</LastPage>
			<ELocationID EIdType="pii">2352</ELocationID>
			
<ELocationID EIdType="doi">10.22034/2015.1.01</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Juanjuan</FirstName>
					<LastName>QIN</LastName>
<Affiliation>Tianjin University of Finance and Economics, TianJin, China</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2015</Year>
					<Month>04</Month>
					<Day>08</Day>
				</PubDate>
			</History>
		<Abstract>This paper investigates an EPQ model with the increasing demand and demand dependent production rate involving the trade credit financing policy, which is seldom reported in the literatures. The model considers the manufacturer was offered by the supplier a delayed payment time. It is assumed that the demand is a linear increasing function of the time and the production rate is proportional to the demand. That is, the production rate is also a linear function of time. This study attempts to offer a best policy for the replenishment cycle and the order quantity for the manufacturer to maximum its profit per cycle. First, the inventory model is developed under the above situation. Second, some useful theoretical results have been derived to characterize the optimal solutions for the inventory system. The Algorithm is proposed to obtain the optimal solutions of the manufacturer. Finally, the numerical examples are carried out to illustrate the theorems, and the sensitivity analysis of the optimal solutions with respect to the parameters of the inventory system is performed. Some important management insights are obtained based on the analysis.</Abstract>
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			<Object Type="keyword">
			<Param Name="value">EPQ</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Trade credit financing</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Increasing demand</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Demand dependent production rate</Param>
			</Object>
		</ObjectList>
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<Article>
<Journal>
				<PublisherName>Kharazmi University</PublisherName>
				<JournalTitle>International Journal of Supply and Operations Management</JournalTitle>
				<Issn>2383-1359</Issn>
				<Volume>2</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2015</Year>
					<Month>05</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>A Fuzzy AHP-TOPSIS Framework for the Risk Assessment of Green Supply Chain Implementation in the Textile Industry</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>548</FirstPage>
			<LastPage>568</LastPage>
			<ELocationID EIdType="pii">2353</ELocationID>
			
<ELocationID EIdType="doi">10.22034/2015.1.02</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Muhammad</FirstName>
					<LastName>Nazam</LastName>
<Affiliation>University of Agriculture, Faisalabad, Pakistan</Affiliation>

</Author>
<Author>
					<FirstName>Jiuping</FirstName>
					<LastName>Xu</LastName>
<Affiliation>Sichuan University, Chengdu, China</Affiliation>

</Author>
<Author>
					<FirstName>Zhimiao</FirstName>
					<LastName>Tao</LastName>
<Affiliation>Sichuan University, Chengdu, China</Affiliation>

</Author>
<Author>
					<FirstName>Jamil</FirstName>
					<LastName>Ahmad</LastName>
<Affiliation>Sichuan University, Chengdu, China</Affiliation>

</Author>
<Author>
					<FirstName>Muhammad</FirstName>
					<LastName>Hashim</LastName>
<Affiliation>National Textile University, Faisalabad, Pakistan</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2015</Year>
					<Month>02</Month>
					<Day>27</Day>
				</PubDate>
			</History>
		<Abstract>In the emerging supply chain environment, green supply chain risk management plays a significant role than ever. Risk is an inherent uncertainty and has tendency to disrupt the typical green supply chain management (GSCM) operations and eventually reduce the success rate of industries. In order to mitigate the consequences, a fuzzy multi-criteria group decision making modeling (FMCGDM) which could evaluate the potential risks in the context of (GSCM) is needed from the industrial point of view. Therefore, this research proposes a combined fuzzy analytical hierarchy process (AHP) to calculate the weight of each risk criterion and sub-criterion and technique for order performance by similarity to ideal solution (TOPSIS) methodology to rank and assess the risks associated with implementation of (GSCM) practices under the fuzzy environment. The proposed fuzzy risk-oriented evaluation model is applied to a practical case of textile manufacturing industry. Finally, the proposed model helps the researchers and practitioners to understand the importance of conducting appropriate risk assessment when implementing green supply chain initiatives.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Fuzzy AHP</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Fuzzy TOPSIS</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Risk assessment</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Green initiatives</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Textile sector</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">http://www.ijsom.com/article_2353_23af4b45f1e166141a790d1a3126e77a.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>Kharazmi University</PublisherName>
				<JournalTitle>International Journal of Supply and Operations Management</JournalTitle>
				<Issn>2383-1359</Issn>
				<Volume>2</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2015</Year>
					<Month>05</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>An Expert System for Intelligent Selection of Proper Particle Swarm Optimization Variants</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>569</FirstPage>
			<LastPage>594</LastPage>
			<ELocationID EIdType="pii">2351</ELocationID>
			
<ELocationID EIdType="doi">10.22034/2015.1.03</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Ellips</FirstName>
					<LastName>Masehian</LastName>
<Affiliation>Tarbiat Modares University, Teahran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Vahid</FirstName>
					<LastName>Eghbal Akhlaghi</LastName>
<Affiliation>Middle East Technical University, Ankara, Turkey</Affiliation>

</Author>
<Author>
					<FirstName>Hossein</FirstName>
					<LastName>Akbaripour</LastName>
<Affiliation>Tarbiat Modares University, Teahran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Davoud</FirstName>
					<LastName>Sedighizadeh</LastName>
<Affiliation>Islamic Azad University, Saveh branch, saveh, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2015</Year>
					<Month>04</Month>
					<Day>16</Day>
				</PubDate>
			</History>
		<Abstract>Regarding the large number of developed Particle Swarm Optimization (PSO) algorithms and the various applications for which PSO has been used, selecting the most suitable variant of PSO for solving a particular optimization problem is a challenge for most researchers. In this paper, using a comprehensive survey and taxonomy on different types of PSO, an Expert System (ES) is designed to identify the most proper PSO for solving different optimization problems. Algorithms are classified according to aspects like particle, variable, process, and swarm. After integrating different acquirable information and forming the knowledge base of the ES consisting 100 rules, the system is able to logically evaluate all the algorithms and report the most appropriate PSO-based approach based on interactions with users, referral to knowledge base and necessary inferences via user interface. In order to examine the validity and efficiency of the system, a comparison is made between the system outputs against the algorithms proposed by newly published articles. The result of this comparison showed that the proposed ES can be considered as a proper tool for finding an appropriate PSO variant that matches the application under consideration.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Particle swarm optimization</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Taxonomy</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">PSO variants</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Expert system</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Knowledge base</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">http://www.ijsom.com/article_2351_0abdc563a06105aee3c6136871c9f4d1.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>Kharazmi University</PublisherName>
				<JournalTitle>International Journal of Supply and Operations Management</JournalTitle>
				<Issn>2383-1359</Issn>
				<Volume>2</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2015</Year>
					<Month>05</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>A Robust Programming Approach to Bi-objective Optimization Model in the Disaster Relief Logistics Response Phase</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>595</FirstPage>
			<LastPage>616</LastPage>
			<ELocationID EIdType="pii">2354</ELocationID>
			
<ELocationID EIdType="doi">10.22034/2015.1.04</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Mohsen</FirstName>
					<LastName>Saffarian</LastName>
<Affiliation>Birjand university of technology, Birjand, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Farnaz</FirstName>
					<LastName>Barzinpour</LastName>
<Affiliation>Iran University of Science and Technology, Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Mohammad Ali</FirstName>
					<LastName>Eghbali</LastName>
<Affiliation>Birjand university of technology, Birjand, Iran</Affiliation>
<Identifier Source="ORCID">0000-0002-0943-3107</Identifier>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2015</Year>
					<Month>04</Month>
					<Day>24</Day>
				</PubDate>
			</History>
		<Abstract>Accidents and natural disasters and crises coming out of them indicate the importance of an integrated planning to reduce their effected. Therefore, disaster relief logistics is one of the main activities in disaster management. In this paper, we study the response phase of the disaster management cycle and a bi-objective model has been developed for relief chain logistic in uncertainty condition including uncertainty in traveling time an also amount of demand in damaged areas. The proposed mathematical model has two objective functions. The first one is to minimize the sum of arrival times to damaged area multiplying by amount of demand and the second objective function is to maximize the minimum ratio of satisfied demands in total period in order to fairness in the distribution of goods. In the proposed model, the problem has been considered periodically and in order to solve the mathematical model, Global Criterion method has been used and a case study has been done at South Khorasan.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Relief logistic</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Cumulative routing</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Periodic approach</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Inventory</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Robust optimization</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">http://www.ijsom.com/article_2354_d254c8a084d4545bd80577481aa03076.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>Kharazmi University</PublisherName>
				<JournalTitle>International Journal of Supply and Operations Management</JournalTitle>
				<Issn>2383-1359</Issn>
				<Volume>2</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2015</Year>
					<Month>05</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Integrated Inventory Model with Controllable Lead Time Involving Investment for Quality Improvement in Supply Chain System</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>617</FirstPage>
			<LastPage>639</LastPage>
			<ELocationID EIdType="pii">2378</ELocationID>
			
<ELocationID EIdType="doi">10.22034/2015.1.05</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>M</FirstName>
					<LastName>Vijayashree</LastName>
<Affiliation>The Gandhigram Rural Institute Deemed- University, Gandhigram, Dindigul, India</Affiliation>

</Author>
<Author>
					<FirstName>R</FirstName>
					<LastName>Uthayakumar</LastName>
<Affiliation>The Gandhigram Rural Institute Deemed- University, Gandhigram, Dindigul, India</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2015</Year>
					<Month>06</Month>
					<Day>22</Day>
				</PubDate>
			</History>
		<Abstract>The purpose of this article is to investigate a two-echelon supply chain inventory problem consisting of a single-vendor and a single-buyer with controllable lead time and investment for quality improvements. This paper presents an integrated vendor-buyer inventory model in order to minimize the sum of the ordering cost, holding cost, setup cost, investment for quality improvement and crashing cost by simultaneously optimizing the optimal order quantity, process quality, lead time and number of deliveries the vendor to the buyer in one production run with the objective of minimizing total relevant cost. Here the lead-time crashing cost has been assumed to be an exponentially function of the lead-time length. The main contribution of proposed model is an efficient iterative algorithm developed to minimize integrated total relevant cost for the single vendor and the single buyer systems with controllable lead time reduction and investment for quality improvements. Graphical representation is also presented to illustrate the proposed model. Numerical examples are presented to illustrate the procedures and results of the proposed algorithm. Matlab coding is also developed to derive the optimal solution and present numerical examples to illustrate the model.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Integrated inventory model</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Vendor buyer coordination</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Controllable lead time crashing cost</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Supply Chain Management</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Investment for quality improvements</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">http://www.ijsom.com/article_2378_3837a451cd0abc5ce4069304c5442c87.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>Kharazmi University</PublisherName>
				<JournalTitle>International Journal of Supply and Operations Management</JournalTitle>
				<Issn>2383-1359</Issn>
				<Volume>2</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2015</Year>
					<Month>05</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>An Integrated Approach for Reliable Facility Location/Network Design Problem with Link Disruption</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>640</FirstPage>
			<LastPage>661</LastPage>
			<ELocationID EIdType="pii">2399</ELocationID>
			
<ELocationID EIdType="doi">10.22034/2015.1.06</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Davood</FirstName>
					<LastName>Shishebori</LastName>
<Affiliation>Department of Industrial Engineering, Yazd University, Yazd, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Abdolsalam</FirstName>
					<LastName>Ghaderi</LastName>
<Affiliation>Department of Industrial engineering, University of Kurdistan, Sanandaj, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2015</Year>
					<Month>05</Month>
					<Day>22</Day>
				</PubDate>
			</History>
		<Abstract>Proposing a robust designed facility location is one of the most effective ways to hedge against unexpected disruptions and failures in a transportation network system. This paper considers the combined facility location/network design problem with regard to transportation link disruptions and develops a mixed integer linear programming formulation to model it. With respect to the probability of link disruptions, the objective function of the model minimizes the total costs, including location costs, link construction costs and also the expected transportation costs. An efficient hybrid algorithm based on LP relaxation and variable neighbourhood search metaheuristic is developed in order to solve the mathematical model. Numerical results demonstrate that the proposed hybrid algorithm has suitable efficiency in terms of duration of solution time and determining excellent solution quality.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Facility location</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Network design</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Reliability</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Link disruption</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">LP relaxation</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Variable neighborhood search</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">http://www.ijsom.com/article_2399_bc7f621451b4f5df308a8e098112185d.pdf</ArchiveCopySource>
</Article>

<Article>
<Journal>
				<PublisherName>Kharazmi University</PublisherName>
				<JournalTitle>International Journal of Supply and Operations Management</JournalTitle>
				<Issn>2383-1359</Issn>
				<Volume>2</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2015</Year>
					<Month>05</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>A Two-warehouse Inventory Model for Deteriorating Items with Permissible Delay under Exponentially Increasing Demand</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>662</FirstPage>
			<LastPage>682</LastPage>
			<ELocationID EIdType="pii">2416</ELocationID>
			
<ELocationID EIdType="doi">10.22034/2015.1.07</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>R</FirstName>
					<LastName>Sundara Rajan</LastName>
<Affiliation>PSNA College of engineering
Dindigul, Silvarpatti, India</Affiliation>

</Author>
<Author>
					<FirstName>R</FirstName>
					<LastName>Uthayakumar</LastName>
<Affiliation>Gandhigram Rural Institute-Deemed University Gandhigram, India</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2015</Year>
					<Month>02</Month>
					<Day>18</Day>
				</PubDate>
			</History>
		<Abstract>In this study, a two-warehouse inventory model with exponentially increasing trend in demand involving different deterioration rates under permissible delay in payment has been studied. Here the scheduling period is assumed to be a variable. The objective of this study is to obtain the condition when to rent a warehouse and the retailer&#039;s optimal replenishment policy that minimizes the total relevant cost. An effective algorithm is designed to obtain the optimal solution of the proposed model. Numerical examples are provided to illustrate the application of the model.Based on the numerical examples, we have concluded that the single warehouse model is less expensive to operate than that of two warehouse model. Sensitivity analysis has been provided and managerial implications are discussed.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Deterioration</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Time-dependent demand</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Two-warehouse</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Permissible delay</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">http://www.ijsom.com/article_2416_5dec707028b05bcbd3a1db5640f842c5.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
