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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>7</Volume>
				<Issue>1</Issue>
				<PubDate PubStatus="epublish">
					<Year>2015</Year>
					<Month>03</Month>
					<Day>21</Day>
				</PubDate>
			</Journal>
<ArticleTitle>A project portfolio selection model with project interaction &amp; resources interdependency consideration using artificial neural networks</ArticleTitle>
<VernacularTitle>ارائة مدلی برای انتخاب سبد پروژه با آثار متقابل و اشتراک منابع بین پروژه ای با استفاده از شبکه های عصبی مصنوعی</VernacularTitle>
			<FirstPage>21</FirstPage>
			<LastPage>42</LastPage>
			<ELocationID EIdType="pii">52106</ELocationID>
			
<ELocationID EIdType="doi">10.22059/imj.2015.52106</ELocationID>
			
			<Language>EN</Language>
<AuthorList>
<Author>
					<FirstName>Behrooz</FirstName>
					<LastName>Dorri</LastName>
<Affiliation>Associate Prof., Management and Accounting Faculty, Shahid Beheshti University, Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Behrang</FirstName>
					<LastName>Asadi</LastName>
<Affiliation>PhD Candidate, Finance, University of Tehran, Tehran, Iran</Affiliation>

</Author>
<Author>
					<FirstName>Sasan</FirstName>
					<LastName>Mazaheri</LastName>
<Affiliation>PhD Candidate, Management- OR, University of Tehran, Tehran, Iran</Affiliation>

</Author>
</AuthorList>
				<PublicationType>Journal Article</PublicationType>
			<History>
				<PubDate PubStatus="received">
					<Year>2014</Year>
					<Month>01</Month>
					<Day>11</Day>
				</PubDate>
			</History>
		<Abstract> A vast number of organizational projects as well as complexity of decision making process can cause particular challenges for project management and its leadership. In order to use organization assets and opportunities efficiently, it is necessary that manager implement a comprehensive multidimensional project portfolio management system that considers economic, social and technical details of the projects. Resource constraint compels managers to select operational proposal projects. Thus managers can maximize organizational utility due to project portfolio’s resource constraint. This study considers the interactive effects of project portfolio evaluation and sharing organizational project resources with respect to its evaluation and choice of the projects.. In this two-step model, first a branch and bound algorithm with resource interaction was utilized to screen maximal portfolio and, in the next step, each portfolio was evaluated based on artificial neural networks to rank the end project portfolios. Also, the ANN scores are strongly correlated with the DEA and COLS efficiency scores.



 </Abstract>
		<ObjectList>
			<Object Type="keyword">
			<Param Name="value">Artificial Neural Network</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">interaction</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">maximal portfolio</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">Project Portfolio Selection</Param>
			</Object>
			<Object Type="keyword">
			<Param Name="value">resource interaction</Param>
			</Object>
		</ObjectList>
<ArchiveCopySource DocType="pdf">https://imj.ut.ac.ir/article_52106_c4bb6c44f847f2656e40614b0b66abc8.pdf</ArchiveCopySource>
</Article>
</ArticleSet>
