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- Publisher Website: 10.1016/j.dss.2005.09.002
- Scopus: eid_2-s2.0-33749848477
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Article: A GIS supported Ant algorithm for the linear feature covering problem with distance constraints
| Title | A GIS supported Ant algorithm for the linear feature covering problem with distance constraints |
|---|---|
| Authors | |
| Keywords | Ant algorithm GIS Linear feature covering problem Two-phase local search |
| Issue Date | 2006 |
| Citation | Decision Support Systems, 2006, v. 42, n. 2, p. 1063-1075 How to Cite? |
| Abstract | This paper analyzes a linear feature covering problem (LFCP) with distance constraints, and characterizes the problem by a fuzzy multi-objective (MO) optimization model. An integrated approach combining an Ant algorithm (LFCP-Ant) and a Geographic Information System (GIS) has been devised to solve the LFCP problem in large scale. The efficacy of the proposed approach is demonstrated using a case study of locating new fire stations in Singapore. A GIS has been used to transform the continuous problem into a discrete one, which is then solved using the LFCP-Ant. This algorithm employs a two-phase local search to improve both search efficiency and precision. © 2005 Elsevier B.V. All rights reserved. |
| Persistent Identifier | http://hdl.handle.net/10722/330079 |
| ISSN | 2023 Impact Factor: 6.7 2023 SCImago Journal Rankings: 2.211 |
| ISI Accession Number ID |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Huang, Bo | - |
| dc.contributor.author | Liu, Nan | - |
| dc.contributor.author | Chandramouli, Magesh | - |
| dc.date.accessioned | 2023-08-09T03:37:38Z | - |
| dc.date.available | 2023-08-09T03:37:38Z | - |
| dc.date.issued | 2006 | - |
| dc.identifier.citation | Decision Support Systems, 2006, v. 42, n. 2, p. 1063-1075 | - |
| dc.identifier.issn | 0167-9236 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/330079 | - |
| dc.description.abstract | This paper analyzes a linear feature covering problem (LFCP) with distance constraints, and characterizes the problem by a fuzzy multi-objective (MO) optimization model. An integrated approach combining an Ant algorithm (LFCP-Ant) and a Geographic Information System (GIS) has been devised to solve the LFCP problem in large scale. The efficacy of the proposed approach is demonstrated using a case study of locating new fire stations in Singapore. A GIS has been used to transform the continuous problem into a discrete one, which is then solved using the LFCP-Ant. This algorithm employs a two-phase local search to improve both search efficiency and precision. © 2005 Elsevier B.V. All rights reserved. | - |
| dc.language | eng | - |
| dc.relation.ispartof | Decision Support Systems | - |
| dc.subject | Ant algorithm | - |
| dc.subject | GIS | - |
| dc.subject | Linear feature covering problem | - |
| dc.subject | Two-phase local search | - |
| dc.title | A GIS supported Ant algorithm for the linear feature covering problem with distance constraints | - |
| dc.type | Article | - |
| dc.description.nature | link_to_subscribed_fulltext | - |
| dc.identifier.doi | 10.1016/j.dss.2005.09.002 | - |
| dc.identifier.scopus | eid_2-s2.0-33749848477 | - |
| dc.identifier.volume | 42 | - |
| dc.identifier.issue | 2 | - |
| dc.identifier.spage | 1063 | - |
| dc.identifier.epage | 1075 | - |
| dc.identifier.isi | WOS:000242209700038 | - |