Cell-transmission-based evacuation planning with rescue teams
The basic ideas of the Cell-Transmission-Model (CTM) by Daganzo (Transp. Res., Part B 28, 269–287, 1994 ) were used in numerous publications dealing with evacuation planning in urban areas. However, none of them consider the assignment of rescue teams which will be needed in case of fire fighting, b...
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| Veröffentlicht in: | Journal of heuristics 2012-06, Vol.18 (3), p.435-471 |
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| creator | Kimms, Alf Maassen, Klaus-Christian |
| description | The basic ideas of the Cell-Transmission-Model (CTM) by Daganzo (Transp. Res., Part B 28, 269–287,
1994
) were used in numerous publications dealing with evacuation planning in urban areas. However, none of them consider the assignment of rescue teams which will be needed in case of fire fighting, bomb disposal or evacuating public buildings like hospitals. In such scenarios, traffic capacities are limited and have to be used as efficiently as possible to reduce danger for the population. Rescue teams usually have to enter the network in opposite driving direction to evacuating vehicles so that difficulties in traffic routing are unavoidable. In this paper, we will introduce an extension for the CTM-based Evacuation Planning Model by Kimms and Maassen (
2012
) which allows to integrate rescue team (contra-)flow into evacuation planning simultaneously. We formulate our approach in such a way that it should be applicable in most real-world cases. We also present a three-staged heuristic procedure which was able to solve real world cases with up to 8750 vehicles within reasonable time. |
| doi_str_mv | 10.1007/s10732-011-9193-z |
| format | Article |
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1994
) were used in numerous publications dealing with evacuation planning in urban areas. However, none of them consider the assignment of rescue teams which will be needed in case of fire fighting, bomb disposal or evacuating public buildings like hospitals. In such scenarios, traffic capacities are limited and have to be used as efficiently as possible to reduce danger for the population. Rescue teams usually have to enter the network in opposite driving direction to evacuating vehicles so that difficulties in traffic routing are unavoidable. In this paper, we will introduce an extension for the CTM-based Evacuation Planning Model by Kimms and Maassen (
2012
) which allows to integrate rescue team (contra-)flow into evacuation planning simultaneously. We formulate our approach in such a way that it should be applicable in most real-world cases. We also present a three-staged heuristic procedure which was able to solve real world cases with up to 8750 vehicles within reasonable time.</description><identifier>ISSN: 1381-1231</identifier><identifier>EISSN: 1572-9397</identifier><identifier>DOI: 10.1007/s10732-011-9193-z</identifier><language>eng</language><publisher>Boston: Springer US</publisher><subject>Artificial Intelligence ; Calculus of Variations and Optimal Control; Optimization ; Contingency planning ; Evacuations & rescues ; Graph representations ; Heuristic ; Management Science ; Mathematical models ; Mathematical programming ; Mathematics ; Mathematics and Statistics ; Operations Research ; Operations Research/Decision Theory ; Optimization ; Planning ; Population ; Problem solving ; Roads & highways ; Simulation ; Studies ; Teams ; Urban areas</subject><ispartof>Journal of heuristics, 2012-06, Vol.18 (3), p.435-471</ispartof><rights>Springer Science+Business Media, LLC 2011</rights><rights>Springer Science+Business Media, LLC 2012</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c347t-e34fd1c38f7e34e941eb6d034cd1ff8c2a0936cc8b37fa8b195f4aa490efbacd3</citedby><cites>FETCH-LOGICAL-c347t-e34fd1c38f7e34e941eb6d034cd1ff8c2a0936cc8b37fa8b195f4aa490efbacd3</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/s10732-011-9193-z$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10732-011-9193-z$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Kimms, Alf</creatorcontrib><creatorcontrib>Maassen, Klaus-Christian</creatorcontrib><title>Cell-transmission-based evacuation planning with rescue teams</title><title>Journal of heuristics</title><addtitle>J Heuristics</addtitle><description>The basic ideas of the Cell-Transmission-Model (CTM) by Daganzo (Transp. Res., Part B 28, 269–287,
1994
) were used in numerous publications dealing with evacuation planning in urban areas. However, none of them consider the assignment of rescue teams which will be needed in case of fire fighting, bomb disposal or evacuating public buildings like hospitals. In such scenarios, traffic capacities are limited and have to be used as efficiently as possible to reduce danger for the population. Rescue teams usually have to enter the network in opposite driving direction to evacuating vehicles so that difficulties in traffic routing are unavoidable. In this paper, we will introduce an extension for the CTM-based Evacuation Planning Model by Kimms and Maassen (
2012
) which allows to integrate rescue team (contra-)flow into evacuation planning simultaneously. We formulate our approach in such a way that it should be applicable in most real-world cases. We also present a three-staged heuristic procedure which was able to solve real world cases with up to 8750 vehicles within reasonable time.</description><subject>Artificial Intelligence</subject><subject>Calculus of Variations and Optimal Control; Optimization</subject><subject>Contingency planning</subject><subject>Evacuations & rescues</subject><subject>Graph representations</subject><subject>Heuristic</subject><subject>Management Science</subject><subject>Mathematical models</subject><subject>Mathematical programming</subject><subject>Mathematics</subject><subject>Mathematics and Statistics</subject><subject>Operations Research</subject><subject>Operations Research/Decision Theory</subject><subject>Optimization</subject><subject>Planning</subject><subject>Population</subject><subject>Problem solving</subject><subject>Roads & highways</subject><subject>Simulation</subject><subject>Studies</subject><subject>Teams</subject><subject>Urban areas</subject><issn>1381-1231</issn><issn>1572-9397</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNp1kD1PwzAQhi0EEiXwA9giMRt8ubS2BwZU8SVVYoHZchy7pEqT4ktA9NfjKgwsTPfq9H5ID2OXIK5BCHlDICQWXABwDRr5_ojNYC4LrlHL46RRAYcC4ZSdEW2EEFrNccZul75t-RBtR9uGqOk7Xlnyde4_rRvtkB75rrVd13Tr_KsZ3vPoyY0-H7zd0jk7CbYlf_F7M_b2cP-6fOKrl8fn5d2KOyzlwD2WoQaHKsgkvS7BV4taYOlqCEG5wgqNC-dUhTJYVYGeh9LaUgsfKutqzNjV1LuL_cfoaTCbfoxdmjQAgIXUKjVkDCaXiz1R9MHsYrO18duAMAdKZqJkEiVzoGT2KVNMGUrebu3jn-Z_Qz8X8Gvr</recordid><startdate>20120601</startdate><enddate>20120601</enddate><creator>Kimms, Alf</creator><creator>Maassen, Klaus-Christian</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>8AL</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>ABUWG</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>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>K7-</scope><scope>L.-</scope><scope>M0C</scope><scope>M0N</scope><scope>P5Z</scope><scope>P62</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PYYUZ</scope><scope>Q9U</scope></search><sort><creationdate>20120601</creationdate><title>Cell-transmission-based evacuation planning with rescue teams</title><author>Kimms, Alf ; Maassen, Klaus-Christian</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c347t-e34fd1c38f7e34e941eb6d034cd1ff8c2a0936cc8b37fa8b195f4aa490efbacd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Artificial Intelligence</topic><topic>Calculus of Variations and Optimal Control; Optimization</topic><topic>Contingency planning</topic><topic>Evacuations & rescues</topic><topic>Graph representations</topic><topic>Heuristic</topic><topic>Management Science</topic><topic>Mathematical models</topic><topic>Mathematical programming</topic><topic>Mathematics</topic><topic>Mathematics and Statistics</topic><topic>Operations Research</topic><topic>Operations Research/Decision Theory</topic><topic>Optimization</topic><topic>Planning</topic><topic>Population</topic><topic>Problem solving</topic><topic>Roads & highways</topic><topic>Simulation</topic><topic>Studies</topic><topic>Teams</topic><topic>Urban areas</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kimms, Alf</creatorcontrib><creatorcontrib>Maassen, Klaus-Christian</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</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>Computing Database (Alumni Edition)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & 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>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</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>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Global</collection><collection>Computing Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & 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>ABI/INFORM Collection China</collection><collection>ProQuest Central Basic</collection><jtitle>Journal of heuristics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kimms, Alf</au><au>Maassen, Klaus-Christian</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Cell-transmission-based evacuation planning with rescue teams</atitle><jtitle>Journal of heuristics</jtitle><stitle>J Heuristics</stitle><date>2012-06-01</date><risdate>2012</risdate><volume>18</volume><issue>3</issue><spage>435</spage><epage>471</epage><pages>435-471</pages><issn>1381-1231</issn><eissn>1572-9397</eissn><abstract>The basic ideas of the Cell-Transmission-Model (CTM) by Daganzo (Transp. Res., Part B 28, 269–287,
1994
) were used in numerous publications dealing with evacuation planning in urban areas. However, none of them consider the assignment of rescue teams which will be needed in case of fire fighting, bomb disposal or evacuating public buildings like hospitals. In such scenarios, traffic capacities are limited and have to be used as efficiently as possible to reduce danger for the population. Rescue teams usually have to enter the network in opposite driving direction to evacuating vehicles so that difficulties in traffic routing are unavoidable. In this paper, we will introduce an extension for the CTM-based Evacuation Planning Model by Kimms and Maassen (
2012
) which allows to integrate rescue team (contra-)flow into evacuation planning simultaneously. We formulate our approach in such a way that it should be applicable in most real-world cases. We also present a three-staged heuristic procedure which was able to solve real world cases with up to 8750 vehicles within reasonable time.</abstract><cop>Boston</cop><pub>Springer US</pub><doi>10.1007/s10732-011-9193-z</doi><tpages>37</tpages></addata></record> |
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| subjects | Artificial Intelligence Calculus of Variations and Optimal Control Optimization Contingency planning Evacuations & rescues Graph representations Heuristic Management Science Mathematical models Mathematical programming Mathematics Mathematics and Statistics Operations Research Operations Research/Decision Theory Optimization Planning Population Problem solving Roads & highways Simulation Studies Teams Urban areas |
| title | Cell-transmission-based evacuation planning with rescue teams |
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