Genetic application in a facility location problem with random demand within queuing framework

In many service and industrial applications of the facility location problem, the number of required facilities along with allocation of the customers to the facilities are the two major questions that need to be answered. In this paper, a facility location problem with stochastic customer demand an...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of intelligent manufacturing 2012-06, Vol.23 (3), p.651-659
Hauptverfasser: Pasandideh, Seyed Hamid Reza, Niaki, Seyed Taghi Akhavan
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 659
container_issue 3
container_start_page 651
container_title Journal of intelligent manufacturing
container_volume 23
creator Pasandideh, Seyed Hamid Reza
Niaki, Seyed Taghi Akhavan
description In many service and industrial applications of the facility location problem, the number of required facilities along with allocation of the customers to the facilities are the two major questions that need to be answered. In this paper, a facility location problem with stochastic customer demand and immobile servers is studied. Two objectives considered in this problem are: (1) minimizing the average customer waiting time and (2) minimizing the average facility idle-time percentage. We formulate this problem using queuing theory and solve the model by a genetic algorithm within the desirability function framework. Several examples are presented to demonstrate the applications of the proposed methodology.
doi_str_mv 10.1007/s10845-010-0416-1
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_1112160928</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2789279981</sourcerecordid><originalsourceid>FETCH-LOGICAL-c316t-31dcb194fd37c8c5daf065253c86bb8f85a732d5dae69562f058741911ed60c03</originalsourceid><addsrcrecordid>eNp1UMtOwzAQtBBIlMIHcLPE2bCbxI5zRBUUpEpc4IrlOHZxyaPYqar-PS7hwIXTrkYzs7NDyDXCLQKUdxFBFpwBAoMCBcMTMkNeZkxiwU_JDCouGOfIz8lFjBsAqKTAGXlf2t6O3lC93bbe6NEPPfU91dRp41s_Hmg7_MLbMNSt7ejejx806L4ZOtrYLi0_UFJ97ezO92vqgu7sfgifl-TM6Tbaq985J2-PD6-LJ7Z6WT4v7lfM5ChGlmNjaqwK1-SlkYY32oHgGc-NFHUtneS6zLMm4VakRzIHXJYFVoi2EWAgn5ObyTdlTCHiqDbDLvTppELEDAVUmUwsnFgmDDEG69Q2-E6Hg0JQxxrVVKNKNapjjQqTJps0MXH7tQ1_nP8VfQPT6HXB</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1112160928</pqid></control><display><type>article</type><title>Genetic application in a facility location problem with random demand within queuing framework</title><source>SpringerLink Journals - AutoHoldings</source><creator>Pasandideh, Seyed Hamid Reza ; Niaki, Seyed Taghi Akhavan</creator><creatorcontrib>Pasandideh, Seyed Hamid Reza ; Niaki, Seyed Taghi Akhavan</creatorcontrib><description>In many service and industrial applications of the facility location problem, the number of required facilities along with allocation of the customers to the facilities are the two major questions that need to be answered. In this paper, a facility location problem with stochastic customer demand and immobile servers is studied. Two objectives considered in this problem are: (1) minimizing the average customer waiting time and (2) minimizing the average facility idle-time percentage. We formulate this problem using queuing theory and solve the model by a genetic algorithm within the desirability function framework. Several examples are presented to demonstrate the applications of the proposed methodology.</description><identifier>ISSN: 0956-5515</identifier><identifier>EISSN: 1572-8145</identifier><identifier>DOI: 10.1007/s10845-010-0416-1</identifier><language>eng</language><publisher>Boston: Springer US</publisher><subject>Analysis ; ATM ; Automated teller machines ; Automation ; Business and Management ; Computer networks ; Control ; Customer services ; Facilities planning ; Genetic algorithms ; Group technology ; Industrial engineering ; Intelligent systems ; Machine learning ; Machines ; Manufacturing ; Mechatronics ; Probability ; Processes ; Production ; Queuing ; Queuing theory ; Robotics ; Scientists ; Servers ; Site selection ; Studies</subject><ispartof>Journal of intelligent manufacturing, 2012-06, Vol.23 (3), p.651-659</ispartof><rights>Springer Science+Business Media, LLC 2010</rights><rights>Springer Science+Business Media, LLC 2012</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c316t-31dcb194fd37c8c5daf065253c86bb8f85a732d5dae69562f058741911ed60c03</citedby><cites>FETCH-LOGICAL-c316t-31dcb194fd37c8c5daf065253c86bb8f85a732d5dae69562f058741911ed60c03</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10845-010-0416-1$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10845-010-0416-1$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Pasandideh, Seyed Hamid Reza</creatorcontrib><creatorcontrib>Niaki, Seyed Taghi Akhavan</creatorcontrib><title>Genetic application in a facility location problem with random demand within queuing framework</title><title>Journal of intelligent manufacturing</title><addtitle>J Intell Manuf</addtitle><description>In many service and industrial applications of the facility location problem, the number of required facilities along with allocation of the customers to the facilities are the two major questions that need to be answered. In this paper, a facility location problem with stochastic customer demand and immobile servers is studied. Two objectives considered in this problem are: (1) minimizing the average customer waiting time and (2) minimizing the average facility idle-time percentage. We formulate this problem using queuing theory and solve the model by a genetic algorithm within the desirability function framework. Several examples are presented to demonstrate the applications of the proposed methodology.</description><subject>Analysis</subject><subject>ATM</subject><subject>Automated teller machines</subject><subject>Automation</subject><subject>Business and Management</subject><subject>Computer networks</subject><subject>Control</subject><subject>Customer services</subject><subject>Facilities planning</subject><subject>Genetic algorithms</subject><subject>Group technology</subject><subject>Industrial engineering</subject><subject>Intelligent systems</subject><subject>Machine learning</subject><subject>Machines</subject><subject>Manufacturing</subject><subject>Mechatronics</subject><subject>Probability</subject><subject>Processes</subject><subject>Production</subject><subject>Queuing</subject><subject>Queuing theory</subject><subject>Robotics</subject><subject>Scientists</subject><subject>Servers</subject><subject>Site selection</subject><subject>Studies</subject><issn>0956-5515</issn><issn>1572-8145</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1UMtOwzAQtBBIlMIHcLPE2bCbxI5zRBUUpEpc4IrlOHZxyaPYqar-PS7hwIXTrkYzs7NDyDXCLQKUdxFBFpwBAoMCBcMTMkNeZkxiwU_JDCouGOfIz8lFjBsAqKTAGXlf2t6O3lC93bbe6NEPPfU91dRp41s_Hmg7_MLbMNSt7ejejx806L4ZOtrYLi0_UFJ97ezO92vqgu7sfgifl-TM6Tbaq985J2-PD6-LJ7Z6WT4v7lfM5ChGlmNjaqwK1-SlkYY32oHgGc-NFHUtneS6zLMm4VakRzIHXJYFVoi2EWAgn5ObyTdlTCHiqDbDLvTppELEDAVUmUwsnFgmDDEG69Q2-E6Hg0JQxxrVVKNKNapjjQqTJps0MXH7tQ1_nP8VfQPT6HXB</recordid><startdate>20120601</startdate><enddate>20120601</enddate><creator>Pasandideh, Seyed Hamid Reza</creator><creator>Niaki, Seyed Taghi Akhavan</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SC</scope><scope>7TB</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>88E</scope><scope>8AL</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FJ</scope><scope>8FK</scope><scope>8FL</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>K7-</scope><scope>K9.</scope><scope>L.-</scope><scope>L6V</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0C</scope><scope>M0N</scope><scope>M0S</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>Q9U</scope></search><sort><creationdate>20120601</creationdate><title>Genetic application in a facility location problem with random demand within queuing framework</title><author>Pasandideh, Seyed Hamid Reza ; Niaki, Seyed Taghi Akhavan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c316t-31dcb194fd37c8c5daf065253c86bb8f85a732d5dae69562f058741911ed60c03</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Analysis</topic><topic>ATM</topic><topic>Automated teller machines</topic><topic>Automation</topic><topic>Business and Management</topic><topic>Computer networks</topic><topic>Control</topic><topic>Customer services</topic><topic>Facilities planning</topic><topic>Genetic algorithms</topic><topic>Group technology</topic><topic>Industrial engineering</topic><topic>Intelligent systems</topic><topic>Machine learning</topic><topic>Machines</topic><topic>Manufacturing</topic><topic>Mechatronics</topic><topic>Probability</topic><topic>Processes</topic><topic>Production</topic><topic>Queuing</topic><topic>Queuing theory</topic><topic>Robotics</topic><topic>Scientists</topic><topic>Servers</topic><topic>Site selection</topic><topic>Studies</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pasandideh, Seyed Hamid Reza</creatorcontrib><creatorcontrib>Niaki, Seyed Taghi Akhavan</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Computer and Information Systems Abstracts</collection><collection>Mechanical &amp; Transportation Engineering Abstracts</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>Computer Science Database</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ABI/INFORM Global</collection><collection>Computing Database</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>Engineering Database</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest One Business</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><jtitle>Journal of intelligent manufacturing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pasandideh, Seyed Hamid Reza</au><au>Niaki, Seyed Taghi Akhavan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Genetic application in a facility location problem with random demand within queuing framework</atitle><jtitle>Journal of intelligent manufacturing</jtitle><stitle>J Intell Manuf</stitle><date>2012-06-01</date><risdate>2012</risdate><volume>23</volume><issue>3</issue><spage>651</spage><epage>659</epage><pages>651-659</pages><issn>0956-5515</issn><eissn>1572-8145</eissn><abstract>In many service and industrial applications of the facility location problem, the number of required facilities along with allocation of the customers to the facilities are the two major questions that need to be answered. In this paper, a facility location problem with stochastic customer demand and immobile servers is studied. Two objectives considered in this problem are: (1) minimizing the average customer waiting time and (2) minimizing the average facility idle-time percentage. We formulate this problem using queuing theory and solve the model by a genetic algorithm within the desirability function framework. Several examples are presented to demonstrate the applications of the proposed methodology.</abstract><cop>Boston</cop><pub>Springer US</pub><doi>10.1007/s10845-010-0416-1</doi><tpages>9</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0956-5515
ispartof Journal of intelligent manufacturing, 2012-06, Vol.23 (3), p.651-659
issn 0956-5515
1572-8145
language eng
recordid cdi_proquest_journals_1112160928
source SpringerLink Journals - AutoHoldings
subjects Analysis
ATM
Automated teller machines
Automation
Business and Management
Computer networks
Control
Customer services
Facilities planning
Genetic algorithms
Group technology
Industrial engineering
Intelligent systems
Machine learning
Machines
Manufacturing
Mechatronics
Probability
Processes
Production
Queuing
Queuing theory
Robotics
Scientists
Servers
Site selection
Studies
title Genetic application in a facility location problem with random demand within queuing framework
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-06T07%3A53%3A05IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Genetic%20application%20in%20a%20facility%20location%20problem%20with%20random%20demand%20within%20queuing%20framework&rft.jtitle=Journal%20of%20intelligent%20manufacturing&rft.au=Pasandideh,%20Seyed%20Hamid%20Reza&rft.date=2012-06-01&rft.volume=23&rft.issue=3&rft.spage=651&rft.epage=659&rft.pages=651-659&rft.issn=0956-5515&rft.eissn=1572-8145&rft_id=info:doi/10.1007/s10845-010-0416-1&rft_dat=%3Cproquest_cross%3E2789279981%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1112160928&rft_id=info:pmid/&rfr_iscdi=true