The Optimization of Passengers’ Travel Time under Express-Slow Mode Based on Suburban Line
The suburban line connects the suburbs and the city centre; it is of huge advantage to attempt the express-slow mode. The passengers’ average travel time is the key factor to reflect the level of rail transport services, especially under the express-slow mode. So it is important to study the passeng...
Gespeichert in:
| Veröffentlicht in: | Mathematical problems in engineering 2016-01, Vol.2016 (2016), p.1-7 |
|---|---|
| Hauptverfasser: | , , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 7 |
|---|---|
| container_issue | 2016 |
| container_start_page | 1 |
| container_title | Mathematical problems in engineering |
| container_volume | 2016 |
| creator | Liu, Zhigang Hu, Hua Yang, Xuechen Ding, Xiaobing Pan, Hanchuan |
| description | The suburban line connects the suburbs and the city centre; it is of huge advantage to attempt the express-slow mode. The passengers’ average travel time is the key factor to reflect the level of rail transport services, especially under the express-slow mode. So it is important to study the passengers’ average travel time under express-slow, which can get benefit on the optimization of operation scheme. First analyze the main factor that affects passengers’ travel time and then mine the dynamic interactive relationship among the factors. Second, a new passengers’ travel time evolution algorithm is proposed after studying the stop schedule and the proportion of express/slow train, and then membrane computing theory algorithm is introduced to solve the model. Finally, Shanghai Metro Line 22 is set as an example to apply the optimization model to calculate the total passengers’ travel time; the result shows that the total average travel time under the express-slow mode can save 1 minute and 38 seconds; the social influence and value of it are very huge. The proposed calculation model is of great help for the decision of stop schedule and provides theoretical and methodological support to determine the proportion of express/slow trains, improves the service level, and enriches and complements the rail transit operation scheme optimization theory system. |
| doi_str_mv | 10.1155/2016/7084353 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1879991408</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>4281580761</sourcerecordid><originalsourceid>FETCH-LOGICAL-c393t-55fd4f68f74a69e34bf65c05ba95bbe1497818fabac7540569612caf4ef23c613</originalsourceid><addsrcrecordid>eNqF0M9Kw0AQBvAgCtbqzbMseBE0die7m2yOWuofqFRoBQ9C2CSzdkua1N3Eqidfw9fzSUxpQfDiaebw-4bh87xDoOcAQvQCCmEvopIzwba8DoiQ-QJ4tN3uNOA-BOxx19tzbkZpAAJkx3uaTJGMFrWZmw9Vm6oklSb3yjksn9G6788vMrHqFQsyMXMkTZmjJYO3hUXn_HFRLcldlSO5VA5z0qbHTdrYVJVkaErc93a0KhwebGbXe7gaTPo3_nB0fdu_GPoZi1ntC6FzrkOpI67CGBlPdSgyKlIVizRF4HEkQWqVqiwSnIowDiHIlOaoA5aFwLreyfruwlYvDbo6mRuXYVGoEqvGJSCjOI6BU9nS4z90VjW2bL9rlaBMSBbRVp2tVWYr5yzqZGHNXNn3BGiyqjpZVZ1sqm756ZpPTZmrpflPH601tga1-tUAgQgk-wHgwoeS</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1850358370</pqid></control><display><type>article</type><title>The Optimization of Passengers’ Travel Time under Express-Slow Mode Based on Suburban Line</title><source>Wiley-Blackwell Open Access Collection</source><source>Alma/SFX Local Collection</source><source>EZB Electronic Journals Library</source><creator>Liu, Zhigang ; Hu, Hua ; Yang, Xuechen ; Ding, Xiaobing ; Pan, Hanchuan</creator><contributor>Tuzcu, Ilhan</contributor><creatorcontrib>Liu, Zhigang ; Hu, Hua ; Yang, Xuechen ; Ding, Xiaobing ; Pan, Hanchuan ; Tuzcu, Ilhan</creatorcontrib><description>The suburban line connects the suburbs and the city centre; it is of huge advantage to attempt the express-slow mode. The passengers’ average travel time is the key factor to reflect the level of rail transport services, especially under the express-slow mode. So it is important to study the passengers’ average travel time under express-slow, which can get benefit on the optimization of operation scheme. First analyze the main factor that affects passengers’ travel time and then mine the dynamic interactive relationship among the factors. Second, a new passengers’ travel time evolution algorithm is proposed after studying the stop schedule and the proportion of express/slow train, and then membrane computing theory algorithm is introduced to solve the model. Finally, Shanghai Metro Line 22 is set as an example to apply the optimization model to calculate the total passengers’ travel time; the result shows that the total average travel time under the express-slow mode can save 1 minute and 38 seconds; the social influence and value of it are very huge. The proposed calculation model is of great help for the decision of stop schedule and provides theoretical and methodological support to determine the proportion of express/slow trains, improves the service level, and enriches and complements the rail transit operation scheme optimization theory system.</description><identifier>ISSN: 1024-123X</identifier><identifier>EISSN: 1563-5147</identifier><identifier>DOI: 10.1155/2016/7084353</identifier><language>eng</language><publisher>Cairo, Egypt: Hindawi Publishing Corporation</publisher><subject>Algorithms ; City centres ; Decision making ; Decision trees ; Engineering ; Evolutionary algorithms ; Integer programming ; Mathematical analysis ; Mathematical models ; Optimization ; Optimization models ; Passengers ; Plugs ; Rail transportation ; Schedules ; Scheduling ; Travel time</subject><ispartof>Mathematical problems in engineering, 2016-01, Vol.2016 (2016), p.1-7</ispartof><rights>Copyright © 2016 Xiaobing Ding et al.</rights><rights>Copyright © 2016 Xiaobing Ding et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c393t-55fd4f68f74a69e34bf65c05ba95bbe1497818fabac7540569612caf4ef23c613</citedby><cites>FETCH-LOGICAL-c393t-55fd4f68f74a69e34bf65c05ba95bbe1497818fabac7540569612caf4ef23c613</cites><orcidid>0000-0003-1739-7684 ; 0000-0002-5647-0445</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27903,27904</link.rule.ids></links><search><contributor>Tuzcu, Ilhan</contributor><creatorcontrib>Liu, Zhigang</creatorcontrib><creatorcontrib>Hu, Hua</creatorcontrib><creatorcontrib>Yang, Xuechen</creatorcontrib><creatorcontrib>Ding, Xiaobing</creatorcontrib><creatorcontrib>Pan, Hanchuan</creatorcontrib><title>The Optimization of Passengers’ Travel Time under Express-Slow Mode Based on Suburban Line</title><title>Mathematical problems in engineering</title><description>The suburban line connects the suburbs and the city centre; it is of huge advantage to attempt the express-slow mode. The passengers’ average travel time is the key factor to reflect the level of rail transport services, especially under the express-slow mode. So it is important to study the passengers’ average travel time under express-slow, which can get benefit on the optimization of operation scheme. First analyze the main factor that affects passengers’ travel time and then mine the dynamic interactive relationship among the factors. Second, a new passengers’ travel time evolution algorithm is proposed after studying the stop schedule and the proportion of express/slow train, and then membrane computing theory algorithm is introduced to solve the model. Finally, Shanghai Metro Line 22 is set as an example to apply the optimization model to calculate the total passengers’ travel time; the result shows that the total average travel time under the express-slow mode can save 1 minute and 38 seconds; the social influence and value of it are very huge. The proposed calculation model is of great help for the decision of stop schedule and provides theoretical and methodological support to determine the proportion of express/slow trains, improves the service level, and enriches and complements the rail transit operation scheme optimization theory system.</description><subject>Algorithms</subject><subject>City centres</subject><subject>Decision making</subject><subject>Decision trees</subject><subject>Engineering</subject><subject>Evolutionary algorithms</subject><subject>Integer programming</subject><subject>Mathematical analysis</subject><subject>Mathematical models</subject><subject>Optimization</subject><subject>Optimization models</subject><subject>Passengers</subject><subject>Plugs</subject><subject>Rail transportation</subject><subject>Schedules</subject><subject>Scheduling</subject><subject>Travel time</subject><issn>1024-123X</issn><issn>1563-5147</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>RHX</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqF0M9Kw0AQBvAgCtbqzbMseBE0die7m2yOWuofqFRoBQ9C2CSzdkua1N3Eqidfw9fzSUxpQfDiaebw-4bh87xDoOcAQvQCCmEvopIzwba8DoiQ-QJ4tN3uNOA-BOxx19tzbkZpAAJkx3uaTJGMFrWZmw9Vm6oklSb3yjksn9G6788vMrHqFQsyMXMkTZmjJYO3hUXn_HFRLcldlSO5VA5z0qbHTdrYVJVkaErc93a0KhwebGbXe7gaTPo3_nB0fdu_GPoZi1ntC6FzrkOpI67CGBlPdSgyKlIVizRF4HEkQWqVqiwSnIowDiHIlOaoA5aFwLreyfruwlYvDbo6mRuXYVGoEqvGJSCjOI6BU9nS4z90VjW2bL9rlaBMSBbRVp2tVWYr5yzqZGHNXNn3BGiyqjpZVZ1sqm756ZpPTZmrpflPH601tga1-tUAgQgk-wHgwoeS</recordid><startdate>20160101</startdate><enddate>20160101</enddate><creator>Liu, Zhigang</creator><creator>Hu, Hua</creator><creator>Yang, Xuechen</creator><creator>Ding, Xiaobing</creator><creator>Pan, Hanchuan</creator><general>Hindawi Publishing Corporation</general><general>Hindawi Limited</general><scope>ADJCN</scope><scope>AHFXO</scope><scope>RHU</scope><scope>RHW</scope><scope>RHX</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>CWDGH</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>KR7</scope><scope>L6V</scope><scope>M7S</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><orcidid>https://orcid.org/0000-0003-1739-7684</orcidid><orcidid>https://orcid.org/0000-0002-5647-0445</orcidid></search><sort><creationdate>20160101</creationdate><title>The Optimization of Passengers’ Travel Time under Express-Slow Mode Based on Suburban Line</title><author>Liu, Zhigang ; Hu, Hua ; Yang, Xuechen ; Ding, Xiaobing ; Pan, Hanchuan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c393t-55fd4f68f74a69e34bf65c05ba95bbe1497818fabac7540569612caf4ef23c613</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Algorithms</topic><topic>City centres</topic><topic>Decision making</topic><topic>Decision trees</topic><topic>Engineering</topic><topic>Evolutionary algorithms</topic><topic>Integer programming</topic><topic>Mathematical analysis</topic><topic>Mathematical models</topic><topic>Optimization</topic><topic>Optimization models</topic><topic>Passengers</topic><topic>Plugs</topic><topic>Rail transportation</topic><topic>Schedules</topic><topic>Scheduling</topic><topic>Travel time</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Zhigang</creatorcontrib><creatorcontrib>Hu, Hua</creatorcontrib><creatorcontrib>Yang, Xuechen</creatorcontrib><creatorcontrib>Ding, Xiaobing</creatorcontrib><creatorcontrib>Pan, Hanchuan</creatorcontrib><collection>الدوريات العلمية والإحصائية - e-Marefa Academic and Statistical Periodicals</collection><collection>معرفة - المحتوى العربي الأكاديمي المتكامل - e-Marefa Academic Complete</collection><collection>Hindawi Publishing Complete</collection><collection>Hindawi Publishing Subscription Journals</collection><collection>Hindawi Publishing Open Access</collection><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</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)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Database (1962 - current)</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>Middle East & Africa Database</collection><collection>ProQuest Central</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer science database</collection><collection>Civil Engineering Abstracts</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Publicly Available Content Database</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>Mathematical problems in engineering</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Zhigang</au><au>Hu, Hua</au><au>Yang, Xuechen</au><au>Ding, Xiaobing</au><au>Pan, Hanchuan</au><au>Tuzcu, Ilhan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>The Optimization of Passengers’ Travel Time under Express-Slow Mode Based on Suburban Line</atitle><jtitle>Mathematical problems in engineering</jtitle><date>2016-01-01</date><risdate>2016</risdate><volume>2016</volume><issue>2016</issue><spage>1</spage><epage>7</epage><pages>1-7</pages><issn>1024-123X</issn><eissn>1563-5147</eissn><abstract>The suburban line connects the suburbs and the city centre; it is of huge advantage to attempt the express-slow mode. The passengers’ average travel time is the key factor to reflect the level of rail transport services, especially under the express-slow mode. So it is important to study the passengers’ average travel time under express-slow, which can get benefit on the optimization of operation scheme. First analyze the main factor that affects passengers’ travel time and then mine the dynamic interactive relationship among the factors. Second, a new passengers’ travel time evolution algorithm is proposed after studying the stop schedule and the proportion of express/slow train, and then membrane computing theory algorithm is introduced to solve the model. Finally, Shanghai Metro Line 22 is set as an example to apply the optimization model to calculate the total passengers’ travel time; the result shows that the total average travel time under the express-slow mode can save 1 minute and 38 seconds; the social influence and value of it are very huge. The proposed calculation model is of great help for the decision of stop schedule and provides theoretical and methodological support to determine the proportion of express/slow trains, improves the service level, and enriches and complements the rail transit operation scheme optimization theory system.</abstract><cop>Cairo, Egypt</cop><pub>Hindawi Publishing Corporation</pub><doi>10.1155/2016/7084353</doi><tpages>7</tpages><orcidid>https://orcid.org/0000-0003-1739-7684</orcidid><orcidid>https://orcid.org/0000-0002-5647-0445</orcidid><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1024-123X |
| ispartof | Mathematical problems in engineering, 2016-01, Vol.2016 (2016), p.1-7 |
| issn | 1024-123X 1563-5147 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1879991408 |
| source | Wiley-Blackwell Open Access Collection; Alma/SFX Local Collection; EZB Electronic Journals Library |
| subjects | Algorithms City centres Decision making Decision trees Engineering Evolutionary algorithms Integer programming Mathematical analysis Mathematical models Optimization Optimization models Passengers Plugs Rail transportation Schedules Scheduling Travel time |
| title | The Optimization of Passengers’ Travel Time under Express-Slow Mode Based on Suburban Line |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-22T17%3A59%3A03IST&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=The%20Optimization%20of%20Passengers%E2%80%99%20Travel%20Time%20under%20Express-Slow%20Mode%20Based%20on%20Suburban%20Line&rft.jtitle=Mathematical%20problems%20in%20engineering&rft.au=Liu,%20Zhigang&rft.date=2016-01-01&rft.volume=2016&rft.issue=2016&rft.spage=1&rft.epage=7&rft.pages=1-7&rft.issn=1024-123X&rft.eissn=1563-5147&rft_id=info:doi/10.1155/2016/7084353&rft_dat=%3Cproquest_cross%3E4281580761%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=1850358370&rft_id=info:pmid/&rfr_iscdi=true |