Emergency vehicle location model and algorithm under uncertainty
Uncertainty is an important feature in the emergency incident management. The emergency event may happen at anytime and anyplace. Based on Laplace criterion, it is supposed that the probabilities of emergency events occurring at any point of the way are the same. Emergency vehicles deal with the eme...
Gespeichert in:
| Hauptverfasser: | , , , |
|---|---|
| Format: | Tagungsbericht |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 4 |
|---|---|
| container_issue | |
| container_start_page | 1 |
| container_title | |
| container_volume | |
| creator | Qing Ye Jianshe Song Zhenglei Yang Lianfeng Wang |
| description | Uncertainty is an important feature in the emergency incident management. The emergency event may happen at anytime and anyplace. Based on Laplace criterion, it is supposed that the probabilities of emergency events occurring at any point of the way are the same. Emergency vehicles deal with the emergency events through the road network. Emergency vehicle location models aiming to a maximum coverage of the target, and demand at any point in the road network are established. According to the characteristics of the design model, the integration of genetic algorithm and tabu search for solving the problem is improved. Finally, a numerical example illustrates the affectivity of the model and algorithm, which can be used in the location of the ambulance and police wagon. |
| doi_str_mv | 10.1109/ICEMMS.2011.6015604 |
| format | Conference Proceeding |
| fullrecord | <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_6015604</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>6015604</ieee_id><sourcerecordid>6015604</sourcerecordid><originalsourceid>FETCH-LOGICAL-i90t-fda752a3ca7dd53e3ffdc0b9ac2837ac2bfcd8636bd7da4989f9577f1503976c3</originalsourceid><addsrcrecordid>eNo1j8tKw0AYhUekoLZ5gm7mBRJnMvedEqIWWlzYfZnM_NOO5CKTKOTtDVjP4jt8mwMHoS0lBaXEPO6q-nD4KEpCaSEJFZLwG5QZpSkvOTdScn2LHv5FmDuUjeMnWSKlKbW4R091B-kMvZvxD1yiawG3g7NTHHrcDR5abHuPbXseUpwuHf7uPaSFDtJkYz_NG7QKth0hu_YaHV_qY_WW799fd9XzPo-GTHnwVonSMmeV94IBC8E70hjrSs3UwiY4ryWTjVfecqNNMEKpQAVhRknH1mj7NxsB4PSVYmfTfLp-Zr_VAkxQ</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Emergency vehicle location model and algorithm under uncertainty</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Qing Ye ; Jianshe Song ; Zhenglei Yang ; Lianfeng Wang</creator><creatorcontrib>Qing Ye ; Jianshe Song ; Zhenglei Yang ; Lianfeng Wang</creatorcontrib><description>Uncertainty is an important feature in the emergency incident management. The emergency event may happen at anytime and anyplace. Based on Laplace criterion, it is supposed that the probabilities of emergency events occurring at any point of the way are the same. Emergency vehicles deal with the emergency events through the road network. Emergency vehicle location models aiming to a maximum coverage of the target, and demand at any point in the road network are established. According to the characteristics of the design model, the integration of genetic algorithm and tabu search for solving the problem is improved. Finally, a numerical example illustrates the affectivity of the model and algorithm, which can be used in the location of the ambulance and police wagon.</description><identifier>ISBN: 1424496659</identifier><identifier>ISBN: 9781424496655</identifier><identifier>EISBN: 9781424496648</identifier><identifier>EISBN: 9781424496662</identifier><identifier>EISBN: 1424496640</identifier><identifier>EISBN: 1424496667</identifier><identifier>DOI: 10.1109/ICEMMS.2011.6015604</identifier><language>eng</language><publisher>IEEE</publisher><subject>Algorithm design and analysis ; emergency systems ; general absolute center ; Genetic algorithms ; network location ; Numerical models ; Roads ; Search problems ; Uncertainty ; Vehicles</subject><ispartof>2011 2nd IEEE International Conference on Emergency Management and Management Sciences, 2011, p.1-4</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6015604$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,778,782,787,788,2054,27908,54903</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6015604$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Qing Ye</creatorcontrib><creatorcontrib>Jianshe Song</creatorcontrib><creatorcontrib>Zhenglei Yang</creatorcontrib><creatorcontrib>Lianfeng Wang</creatorcontrib><title>Emergency vehicle location model and algorithm under uncertainty</title><title>2011 2nd IEEE International Conference on Emergency Management and Management Sciences</title><addtitle>ICEMMS</addtitle><description>Uncertainty is an important feature in the emergency incident management. The emergency event may happen at anytime and anyplace. Based on Laplace criterion, it is supposed that the probabilities of emergency events occurring at any point of the way are the same. Emergency vehicles deal with the emergency events through the road network. Emergency vehicle location models aiming to a maximum coverage of the target, and demand at any point in the road network are established. According to the characteristics of the design model, the integration of genetic algorithm and tabu search for solving the problem is improved. Finally, a numerical example illustrates the affectivity of the model and algorithm, which can be used in the location of the ambulance and police wagon.</description><subject>Algorithm design and analysis</subject><subject>emergency systems</subject><subject>general absolute center</subject><subject>Genetic algorithms</subject><subject>network location</subject><subject>Numerical models</subject><subject>Roads</subject><subject>Search problems</subject><subject>Uncertainty</subject><subject>Vehicles</subject><isbn>1424496659</isbn><isbn>9781424496655</isbn><isbn>9781424496648</isbn><isbn>9781424496662</isbn><isbn>1424496640</isbn><isbn>1424496667</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1j8tKw0AYhUekoLZ5gm7mBRJnMvedEqIWWlzYfZnM_NOO5CKTKOTtDVjP4jt8mwMHoS0lBaXEPO6q-nD4KEpCaSEJFZLwG5QZpSkvOTdScn2LHv5FmDuUjeMnWSKlKbW4R091B-kMvZvxD1yiawG3g7NTHHrcDR5abHuPbXseUpwuHf7uPaSFDtJkYz_NG7QKth0hu_YaHV_qY_WW799fd9XzPo-GTHnwVonSMmeV94IBC8E70hjrSs3UwiY4ryWTjVfecqNNMEKpQAVhRknH1mj7NxsB4PSVYmfTfLp-Zr_VAkxQ</recordid><startdate>201108</startdate><enddate>201108</enddate><creator>Qing Ye</creator><creator>Jianshe Song</creator><creator>Zhenglei Yang</creator><creator>Lianfeng Wang</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201108</creationdate><title>Emergency vehicle location model and algorithm under uncertainty</title><author>Qing Ye ; Jianshe Song ; Zhenglei Yang ; Lianfeng Wang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-fda752a3ca7dd53e3ffdc0b9ac2837ac2bfcd8636bd7da4989f9577f1503976c3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Algorithm design and analysis</topic><topic>emergency systems</topic><topic>general absolute center</topic><topic>Genetic algorithms</topic><topic>network location</topic><topic>Numerical models</topic><topic>Roads</topic><topic>Search problems</topic><topic>Uncertainty</topic><topic>Vehicles</topic><toplevel>online_resources</toplevel><creatorcontrib>Qing Ye</creatorcontrib><creatorcontrib>Jianshe Song</creatorcontrib><creatorcontrib>Zhenglei Yang</creatorcontrib><creatorcontrib>Lianfeng Wang</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Qing Ye</au><au>Jianshe Song</au><au>Zhenglei Yang</au><au>Lianfeng Wang</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Emergency vehicle location model and algorithm under uncertainty</atitle><btitle>2011 2nd IEEE International Conference on Emergency Management and Management Sciences</btitle><stitle>ICEMMS</stitle><date>2011-08</date><risdate>2011</risdate><spage>1</spage><epage>4</epage><pages>1-4</pages><isbn>1424496659</isbn><isbn>9781424496655</isbn><eisbn>9781424496648</eisbn><eisbn>9781424496662</eisbn><eisbn>1424496640</eisbn><eisbn>1424496667</eisbn><abstract>Uncertainty is an important feature in the emergency incident management. The emergency event may happen at anytime and anyplace. Based on Laplace criterion, it is supposed that the probabilities of emergency events occurring at any point of the way are the same. Emergency vehicles deal with the emergency events through the road network. Emergency vehicle location models aiming to a maximum coverage of the target, and demand at any point in the road network are established. According to the characteristics of the design model, the integration of genetic algorithm and tabu search for solving the problem is improved. Finally, a numerical example illustrates the affectivity of the model and algorithm, which can be used in the location of the ambulance and police wagon.</abstract><pub>IEEE</pub><doi>10.1109/ICEMMS.2011.6015604</doi><tpages>4</tpages></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | ISBN: 1424496659 |
| ispartof | 2011 2nd IEEE International Conference on Emergency Management and Management Sciences, 2011, p.1-4 |
| issn | |
| language | eng |
| recordid | cdi_ieee_primary_6015604 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Algorithm design and analysis emergency systems general absolute center Genetic algorithms network location Numerical models Roads Search problems Uncertainty Vehicles |
| title | Emergency vehicle location model and algorithm under uncertainty |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-16T16%3A32%3A13IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Emergency%20vehicle%20location%20model%20and%20algorithm%20under%20uncertainty&rft.btitle=2011%202nd%20IEEE%20International%20Conference%20on%20Emergency%20Management%20and%20Management%20Sciences&rft.au=Qing%20Ye&rft.date=2011-08&rft.spage=1&rft.epage=4&rft.pages=1-4&rft.isbn=1424496659&rft.isbn_list=9781424496655&rft_id=info:doi/10.1109/ICEMMS.2011.6015604&rft_dat=%3Cieee_6IE%3E6015604%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&rft.eisbn=9781424496648&rft.eisbn_list=9781424496662&rft.eisbn_list=1424496640&rft.eisbn_list=1424496667&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=6015604&rfr_iscdi=true |