Multi-Objective Optimization of Freeway Network Traffic Flow Using Particle Swarm Optimization
A multi-objective optimization problem of ramp metering and dynamic route guidance is presented. The problem domain, a freeway integration control application considers the efficiency and equity of system, is formulated as a multi-objective optimization problem. The Gini coefficient is adopted in th...
Gespeichert in:
Veröffentlicht in: | Applied Mechanics and Materials 2015-01, Vol.713-715 (Mechatronics Engineering and Modern Information Technologies in Industrial Engineering), p.1777-1781 |
---|---|
1. Verfasser: | |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 1781 |
---|---|
container_issue | Mechatronics Engineering and Modern Information Technologies in Industrial Engineering |
container_start_page | 1777 |
container_title | Applied Mechanics and Materials |
container_volume | 713-715 |
creator | Wen, Kai Ge |
description | A multi-objective optimization problem of ramp metering and dynamic route guidance is presented. The problem domain, a freeway integration control application considers the efficiency and equity of system, is formulated as a multi-objective optimization problem. The Gini coefficient is adopted in this study as an indicator of equity. The control strategy’s effect is demonstrated through its application to the simple freeway network. Analyses of simulation results using this approach show the equity of the system have a significant improvement over traditional control, especially for the case of large traffic demand. Using the multi-objective optimization approach, the Gini coefficient of the network has been reduced by 55% compared to traditional method. |
doi_str_mv | 10.4028/www.scientific.net/AMM.713-715.1777 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1864535180</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>4203368921</sourcerecordid><originalsourceid>FETCH-LOGICAL-c2497-e695ced7244bfe977330eb026338f9bbb5b26439d05348553e28e4be2cc2c5613</originalsourceid><addsrcrecordid>eNqVkVtrFDEUgINWsLb9DwFfBJlp7pfHsnRV6LqFtq-GTHpGs87OrEm2Q_31pq7g5c2HQx7Ox5cDH0JvKWkFYeZ8nuc2hwhjiX0M7Qjl_GK1ajXljaaypVrrZ-iYKsUaLQx7js6sNpxwwyXX1h793JHGcq5eolc5bwhRggpzjD6t9kOJzbrbQCjxAfB6V-I2fvclTiOeerxMALN_xB-hzFP6im-T7-sNeDlMM77LcfyMr30qMQyAb2aftn8ZTtGL3g8Zzn69J-hueXm7eN9crd99WFxcNYEJqxtQVga410yIrgerNecEOsIU56a3XdfJjinB7T2RXBgpOTADogMWAgtSUX6C3hy8uzR920MubhtzgGHwI0z77KhRQnJJDano63_QzbRPY72uUkwqTZhWlVocqJCmnBP0bpfi1qdHR4l7auJqE_e7iatNXG3iapM60j01qZbLg6UkP-YC4csfn_2H5weo8J0c</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1825670276</pqid></control><display><type>article</type><title>Multi-Objective Optimization of Freeway Network Traffic Flow Using Particle Swarm Optimization</title><source>Scientific.net Journals</source><creator>Wen, Kai Ge</creator><creatorcontrib>Wen, Kai Ge</creatorcontrib><description>A multi-objective optimization problem of ramp metering and dynamic route guidance is presented. The problem domain, a freeway integration control application considers the efficiency and equity of system, is formulated as a multi-objective optimization problem. The Gini coefficient is adopted in this study as an indicator of equity. The control strategy’s effect is demonstrated through its application to the simple freeway network. Analyses of simulation results using this approach show the equity of the system have a significant improvement over traditional control, especially for the case of large traffic demand. Using the multi-objective optimization approach, the Gini coefficient of the network has been reduced by 55% compared to traditional method.</description><identifier>ISSN: 1660-9336</identifier><identifier>ISSN: 1662-7482</identifier><identifier>ISBN: 9783038353799</identifier><identifier>ISBN: 3038353795</identifier><identifier>EISSN: 1662-7482</identifier><identifier>DOI: 10.4028/www.scientific.net/AMM.713-715.1777</identifier><language>eng</language><publisher>Zurich: Trans Tech Publications Ltd</publisher><subject>Coefficients ; Control systems ; Freeways ; Multiple objective analysis ; Networks ; Optimization ; Ramps ; Traffic flow</subject><ispartof>Applied Mechanics and Materials, 2015-01, Vol.713-715 (Mechatronics Engineering and Modern Information Technologies in Industrial Engineering), p.1777-1781</ispartof><rights>2015 Trans Tech Publications Ltd</rights><rights>Copyright Trans Tech Publications Ltd. Jan 2015</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2497-e695ced7244bfe977330eb026338f9bbb5b26439d05348553e28e4be2cc2c5613</citedby><cites>FETCH-LOGICAL-c2497-e695ced7244bfe977330eb026338f9bbb5b26439d05348553e28e4be2cc2c5613</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Uhttps://www.scientific.net/Image/TitleCover/3744?width=600</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids></links><search><creatorcontrib>Wen, Kai Ge</creatorcontrib><title>Multi-Objective Optimization of Freeway Network Traffic Flow Using Particle Swarm Optimization</title><title>Applied Mechanics and Materials</title><description>A multi-objective optimization problem of ramp metering and dynamic route guidance is presented. The problem domain, a freeway integration control application considers the efficiency and equity of system, is formulated as a multi-objective optimization problem. The Gini coefficient is adopted in this study as an indicator of equity. The control strategy’s effect is demonstrated through its application to the simple freeway network. Analyses of simulation results using this approach show the equity of the system have a significant improvement over traditional control, especially for the case of large traffic demand. Using the multi-objective optimization approach, the Gini coefficient of the network has been reduced by 55% compared to traditional method.</description><subject>Coefficients</subject><subject>Control systems</subject><subject>Freeways</subject><subject>Multiple objective analysis</subject><subject>Networks</subject><subject>Optimization</subject><subject>Ramps</subject><subject>Traffic flow</subject><issn>1660-9336</issn><issn>1662-7482</issn><issn>1662-7482</issn><isbn>9783038353799</isbn><isbn>3038353795</isbn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNqVkVtrFDEUgINWsLb9DwFfBJlp7pfHsnRV6LqFtq-GTHpGs87OrEm2Q_31pq7g5c2HQx7Ox5cDH0JvKWkFYeZ8nuc2hwhjiX0M7Qjl_GK1ajXljaaypVrrZ-iYKsUaLQx7js6sNpxwwyXX1h793JHGcq5eolc5bwhRggpzjD6t9kOJzbrbQCjxAfB6V-I2fvclTiOeerxMALN_xB-hzFP6im-T7-sNeDlMM77LcfyMr30qMQyAb2aftn8ZTtGL3g8Zzn69J-hueXm7eN9crd99WFxcNYEJqxtQVga410yIrgerNecEOsIU56a3XdfJjinB7T2RXBgpOTADogMWAgtSUX6C3hy8uzR920MubhtzgGHwI0z77KhRQnJJDano63_QzbRPY72uUkwqTZhWlVocqJCmnBP0bpfi1qdHR4l7auJqE_e7iatNXG3iapM60j01qZbLg6UkP-YC4csfn_2H5weo8J0c</recordid><startdate>20150101</startdate><enddate>20150101</enddate><creator>Wen, Kai Ge</creator><general>Trans Tech Publications Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SR</scope><scope>7TB</scope><scope>8BQ</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>BFMQW</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>HCIFZ</scope><scope>JG9</scope><scope>KB.</scope><scope>KR7</scope><scope>L6V</scope><scope>M7S</scope><scope>PDBOC</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20150101</creationdate><title>Multi-Objective Optimization of Freeway Network Traffic Flow Using Particle Swarm Optimization</title><author>Wen, Kai Ge</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2497-e695ced7244bfe977330eb026338f9bbb5b26439d05348553e28e4be2cc2c5613</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Coefficients</topic><topic>Control systems</topic><topic>Freeways</topic><topic>Multiple objective analysis</topic><topic>Networks</topic><topic>Optimization</topic><topic>Ramps</topic><topic>Traffic flow</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wen, Kai Ge</creatorcontrib><collection>CrossRef</collection><collection>Engineered Materials Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>METADEX</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>Continental Europe Database</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>SciTech Premium Collection</collection><collection>Materials Research Database</collection><collection>Materials Science Database</collection><collection>Civil Engineering Abstracts</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Materials Science Collection</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><jtitle>Applied Mechanics and Materials</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wen, Kai Ge</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Multi-Objective Optimization of Freeway Network Traffic Flow Using Particle Swarm Optimization</atitle><jtitle>Applied Mechanics and Materials</jtitle><date>2015-01-01</date><risdate>2015</risdate><volume>713-715</volume><issue>Mechatronics Engineering and Modern Information Technologies in Industrial Engineering</issue><spage>1777</spage><epage>1781</epage><pages>1777-1781</pages><issn>1660-9336</issn><issn>1662-7482</issn><eissn>1662-7482</eissn><isbn>9783038353799</isbn><isbn>3038353795</isbn><abstract>A multi-objective optimization problem of ramp metering and dynamic route guidance is presented. The problem domain, a freeway integration control application considers the efficiency and equity of system, is formulated as a multi-objective optimization problem. The Gini coefficient is adopted in this study as an indicator of equity. The control strategy’s effect is demonstrated through its application to the simple freeway network. Analyses of simulation results using this approach show the equity of the system have a significant improvement over traditional control, especially for the case of large traffic demand. Using the multi-objective optimization approach, the Gini coefficient of the network has been reduced by 55% compared to traditional method.</abstract><cop>Zurich</cop><pub>Trans Tech Publications Ltd</pub><doi>10.4028/www.scientific.net/AMM.713-715.1777</doi><tpages>5</tpages></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1660-9336 |
ispartof | Applied Mechanics and Materials, 2015-01, Vol.713-715 (Mechatronics Engineering and Modern Information Technologies in Industrial Engineering), p.1777-1781 |
issn | 1660-9336 1662-7482 1662-7482 |
language | eng |
recordid | cdi_proquest_miscellaneous_1864535180 |
source | Scientific.net Journals |
subjects | Coefficients Control systems Freeways Multiple objective analysis Networks Optimization Ramps Traffic flow |
title | Multi-Objective Optimization of Freeway Network Traffic Flow Using Particle Swarm Optimization |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-07T22%3A39%3A14IST&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=Multi-Objective%20Optimization%20of%20Freeway%20Network%20Traffic%20Flow%20Using%20Particle%20Swarm%20Optimization&rft.jtitle=Applied%20Mechanics%20and%20Materials&rft.au=Wen,%20Kai%20Ge&rft.date=2015-01-01&rft.volume=713-715&rft.issue=Mechatronics%20Engineering%20and%20Modern%20Information%20Technologies%20in%20Industrial%20Engineering&rft.spage=1777&rft.epage=1781&rft.pages=1777-1781&rft.issn=1660-9336&rft.eissn=1662-7482&rft.isbn=9783038353799&rft.isbn_list=3038353795&rft_id=info:doi/10.4028/www.scientific.net/AMM.713-715.1777&rft_dat=%3Cproquest_cross%3E4203368921%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=1825670276&rft_id=info:pmid/&rfr_iscdi=true |