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<ArticleSet>
<Article>
<Journal>
				<PublisherName>Kharazmi University</PublisherName>
				<JournalTitle>International Journal of Supply and Operations Management</JournalTitle>
				<Issn>2383-1359</Issn>
				<Volume>4</Volume>
				<Issue>2</Issue>
				<PubDate PubStatus="epublish">
					<Year>2017</Year>
					<Month>05</Month>
					<Day>01</Day>
				</PubDate>
			</Journal>
<ArticleTitle>Design of Forward/reverse Logistics with Environmental Consideration</ArticleTitle>
<VernacularTitle></VernacularTitle>
			<FirstPage>115</FirstPage>
			<LastPage>132</LastPage>
			<ELocationID EIdType="pii">2726</ELocationID>
			
<ELocationID EIdType="doi">10.22034/2017.2.02</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Masoud</FirstName>
					<LastName>Rabbani</LastName>
<Affiliation>School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Niloufar</FirstName>
					<LastName>Akbarian Saravi</LastName>
<Affiliation>School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Hamed</FirstName>
					<LastName>Farrokhi-Asl</LastName>
<Affiliation>School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2017</Year>
					<Month>03</Month>
					<Day>25</Day>
				</PubDate>
			</History>
		    <Abstract>Growth of environmental issues has caused to consider various factors that influence on condition of environment. Green supply chain has absorbed care of researchers because of its considerable impacts on environment. In this regard, this study designs the forward/revers logistics network by putting emphasis on environmental aspects in its model such as quantity of CO2 emission. In this logistics network, three objective functions such as minimizing the total cost and quantity of CO2 emission as well as maximizing the satisfaction of customers have been considered, simultaneously. Because of considering of three objective functions in this model, multi objective optimization methods persuade the researchers to implement them. Non-dominated sorting genetic algorithms (NSGA-ӀӀ) and Multi-objective particle swarm optimization (MOPSO) are proposed to cope with this problem. The results acquired from experiments on several test problems are verified by GAMS software. Finally, the results obtained through experiments on different problems verify the superiority of NSGA-ӀӀ over MOPSO in terms of all comparison metrics.</Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Green supply chain</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">CO2 emission</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Forward/reverse logistics</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Environmental issues</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Multi objective optimization</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">http://www.ijsom.com/article_2726_b1c00bcd4b5183705c134b3365f8c45e.pdf</ArchiveCopySource>
</Article>
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