Dynamic ant colony optimisation for TSP
Ants exhibit collective behaviour in performing tasks that cannot be carried out by an individual ant. When ants are working, they must communicate with each other through a kind of chemical substance—pheromones. Ants look for food and lay the way back to their nest with pheromones, and the other an...
Gespeichert in:
| Veröffentlicht in: | International journal of advanced manufacturing technology 2003-11, Vol.22 (7-8), p.528-533 |
|---|---|
| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 533 |
|---|---|
| container_issue | 7-8 |
| container_start_page | 528 |
| container_title | International journal of advanced manufacturing technology |
| container_volume | 22 |
| creator | Li, Yong Gong, Shihua |
| description | Ants exhibit collective behaviour in performing tasks that cannot be carried out by an individual ant. When ants are working, they must communicate with each other through a kind of chemical substance—pheromones. Ants look for food and lay the way back to their nest with pheromones, and the other ants can follow the pheromone to find the food efficiently. Using the analogy of foraging behaviour and pheromones, Marco Dorigo proposed the ant algorithm and applied it to solving the travelling salesman problem (TSP) and solving job-shop scheduling. In this paper, we simulate real ants with more aspects. Updating of pheromones is more likely to be the real situation in the natural world. Our algorithm shows a better performance than the original algorithm. |
| doi_str_mv | 10.1007/s00170-002-1478-9 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2262521851</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2262521851</sourcerecordid><originalsourceid>FETCH-LOGICAL-c301t-ac1c3a374f8271965364e1b4cc3fb24365cdf3d175bebfb6d6421551cf8dec313</originalsourceid><addsrcrecordid>eNotkM1KAzEYRYMoOFYfwN2AC1fRfPny16XUXygoWNchk0lgSjupyXQxb-8MdXU3h3vgEHIL7AEY04-FMdCMMsYpCG3o8oxUIBApMpDnpGJcGYpamUtyVcp2ohUoU5H757F3-87Xrh9qn3apH-t0GLp9V9zQpb6OKdeb769rchHdroSb_12Qn9eXzeqdrj_fPlZPa-on0UCdB48OtYiGa1gqiUoEaIT3GBsuUEnfRmxByyY0sVGtEhykBB9NGzwCLsjd6feQ0-8xlMFu0zH3k9JyrrjkYORMwYnyOZWSQ7SH3O1dHi0wO_ewpx526mHnHnaJf-dpUVM</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2262521851</pqid></control><display><type>article</type><title>Dynamic ant colony optimisation for TSP</title><source>SpringerLink Journals</source><creator>Li, Yong ; Gong, Shihua</creator><creatorcontrib>Li, Yong ; Gong, Shihua</creatorcontrib><description>Ants exhibit collective behaviour in performing tasks that cannot be carried out by an individual ant. When ants are working, they must communicate with each other through a kind of chemical substance—pheromones. Ants look for food and lay the way back to their nest with pheromones, and the other ants can follow the pheromone to find the food efficiently. Using the analogy of foraging behaviour and pheromones, Marco Dorigo proposed the ant algorithm and applied it to solving the travelling salesman problem (TSP) and solving job-shop scheduling. In this paper, we simulate real ants with more aspects. Updating of pheromones is more likely to be the real situation in the natural world. Our algorithm shows a better performance than the original algorithm.</description><identifier>ISSN: 0268-3768</identifier><identifier>EISSN: 1433-3015</identifier><identifier>DOI: 10.1007/s00170-002-1478-9</identifier><language>eng</language><publisher>Heidelberg: Springer Nature B.V</publisher><subject>Algorithms ; Ant colony optimization ; Computer simulation ; Food ; Job shop scheduling ; Organic chemistry ; Pheromones ; Traveling salesman problem</subject><ispartof>International journal of advanced manufacturing technology, 2003-11, Vol.22 (7-8), p.528-533</ispartof><rights>The International Journal of Advanced Manufacturing Technology is a copyright of Springer, (2003). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c301t-ac1c3a374f8271965364e1b4cc3fb24365cdf3d175bebfb6d6421551cf8dec313</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Li, Yong</creatorcontrib><creatorcontrib>Gong, Shihua</creatorcontrib><title>Dynamic ant colony optimisation for TSP</title><title>International journal of advanced manufacturing technology</title><description>Ants exhibit collective behaviour in performing tasks that cannot be carried out by an individual ant. When ants are working, they must communicate with each other through a kind of chemical substance—pheromones. Ants look for food and lay the way back to their nest with pheromones, and the other ants can follow the pheromone to find the food efficiently. Using the analogy of foraging behaviour and pheromones, Marco Dorigo proposed the ant algorithm and applied it to solving the travelling salesman problem (TSP) and solving job-shop scheduling. In this paper, we simulate real ants with more aspects. Updating of pheromones is more likely to be the real situation in the natural world. Our algorithm shows a better performance than the original algorithm.</description><subject>Algorithms</subject><subject>Ant colony optimization</subject><subject>Computer simulation</subject><subject>Food</subject><subject>Job shop scheduling</subject><subject>Organic chemistry</subject><subject>Pheromones</subject><subject>Traveling salesman problem</subject><issn>0268-3768</issn><issn>1433-3015</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2003</creationdate><recordtype>article</recordtype><sourceid>BENPR</sourceid><recordid>eNotkM1KAzEYRYMoOFYfwN2AC1fRfPny16XUXygoWNchk0lgSjupyXQxb-8MdXU3h3vgEHIL7AEY04-FMdCMMsYpCG3o8oxUIBApMpDnpGJcGYpamUtyVcp2ohUoU5H757F3-87Xrh9qn3apH-t0GLp9V9zQpb6OKdeb769rchHdroSb_12Qn9eXzeqdrj_fPlZPa-on0UCdB48OtYiGa1gqiUoEaIT3GBsuUEnfRmxByyY0sVGtEhykBB9NGzwCLsjd6feQ0-8xlMFu0zH3k9JyrrjkYORMwYnyOZWSQ7SH3O1dHi0wO_ewpx526mHnHnaJf-dpUVM</recordid><startdate>20031101</startdate><enddate>20031101</enddate><creator>Li, Yong</creator><creator>Gong, Shihua</creator><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20031101</creationdate><title>Dynamic ant colony optimisation for TSP</title><author>Li, Yong ; Gong, Shihua</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c301t-ac1c3a374f8271965364e1b4cc3fb24365cdf3d175bebfb6d6421551cf8dec313</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2003</creationdate><topic>Algorithms</topic><topic>Ant colony optimization</topic><topic>Computer simulation</topic><topic>Food</topic><topic>Job shop scheduling</topic><topic>Organic chemistry</topic><topic>Pheromones</topic><topic>Traveling salesman problem</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Li, Yong</creatorcontrib><creatorcontrib>Gong, Shihua</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering 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>International journal of advanced manufacturing technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Li, Yong</au><au>Gong, Shihua</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Dynamic ant colony optimisation for TSP</atitle><jtitle>International journal of advanced manufacturing technology</jtitle><date>2003-11-01</date><risdate>2003</risdate><volume>22</volume><issue>7-8</issue><spage>528</spage><epage>533</epage><pages>528-533</pages><issn>0268-3768</issn><eissn>1433-3015</eissn><abstract>Ants exhibit collective behaviour in performing tasks that cannot be carried out by an individual ant. When ants are working, they must communicate with each other through a kind of chemical substance—pheromones. Ants look for food and lay the way back to their nest with pheromones, and the other ants can follow the pheromone to find the food efficiently. Using the analogy of foraging behaviour and pheromones, Marco Dorigo proposed the ant algorithm and applied it to solving the travelling salesman problem (TSP) and solving job-shop scheduling. In this paper, we simulate real ants with more aspects. Updating of pheromones is more likely to be the real situation in the natural world. Our algorithm shows a better performance than the original algorithm.</abstract><cop>Heidelberg</cop><pub>Springer Nature B.V</pub><doi>10.1007/s00170-002-1478-9</doi><tpages>6</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0268-3768 |
| ispartof | International journal of advanced manufacturing technology, 2003-11, Vol.22 (7-8), p.528-533 |
| issn | 0268-3768 1433-3015 |
| language | eng |
| recordid | cdi_proquest_journals_2262521851 |
| source | SpringerLink Journals |
| subjects | Algorithms Ant colony optimization Computer simulation Food Job shop scheduling Organic chemistry Pheromones Traveling salesman problem |
| title | Dynamic ant colony optimisation for TSP |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-30T05%3A01%3A40IST&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=Dynamic%20ant%20colony%20optimisation%20for%20TSP&rft.jtitle=International%20journal%20of%20advanced%20manufacturing%20technology&rft.au=Li,%20Yong&rft.date=2003-11-01&rft.volume=22&rft.issue=7-8&rft.spage=528&rft.epage=533&rft.pages=528-533&rft.issn=0268-3768&rft.eissn=1433-3015&rft_id=info:doi/10.1007/s00170-002-1478-9&rft_dat=%3Cproquest_cross%3E2262521851%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=2262521851&rft_id=info:pmid/&rfr_iscdi=true |