Ant Colony Optimisation Algorithm for the Facility Localisation Problem
This article describes a new ant colony optimisation algorithm for the facility localisation problem with a new heuristic pattern proposed by the author, which consists of three parts: the function of the average cost of client servicing; the total minimum cost of servicing from a site, which is sel...
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| Format: | Article |
| Language: | English |
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Sciendo
2018-01-01
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| Series: | Technical Transactions |
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| Online Access: | https://doi.org/10.4467/2353737XCT.18.008.7959 |
| _version_ | 1797387212434702336 |
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| author | Schiff Krzysztof |
| author_facet | Schiff Krzysztof |
| author_sort | Schiff Krzysztof |
| collection | DOAJ |
| description | This article describes a new ant colony optimisation algorithm for the facility localisation problem with a new heuristic pattern proposed by the author, which consists of three parts: the function of the average cost of client servicing; the total minimum cost of servicing from a site, which is selected and included into the solution; the function of improving the cost of already serviced clients. In this comparison, simulations were presented, and two parameters were observed: the number of sites and the cost of client servicing. The new algorithm allowed to improve the solution in both of these parameters. |
| first_indexed | 2024-03-08T22:20:34Z |
| format | Article |
| id | doaj.art-bab4b68e3041467da8c2810c5b828241 |
| institution | Directory Open Access Journal |
| issn | 2353-737X |
| language | English |
| last_indexed | 2024-03-08T22:20:34Z |
| publishDate | 2018-01-01 |
| publisher | Sciendo |
| record_format | Article |
| series | Technical Transactions |
| spelling | doaj.art-bab4b68e3041467da8c2810c5b8282412023-12-18T12:46:17ZengSciendoTechnical Transactions2353-737X2018-01-01115110311210.4467/2353737XCT.18.008.7959Ant Colony Optimisation Algorithm for the Facility Localisation ProblemSchiff Krzysztof0Department of Automatic Control and Information Technology, Faculty of Electrical Engineering, Cracow University of TechnologyThis article describes a new ant colony optimisation algorithm for the facility localisation problem with a new heuristic pattern proposed by the author, which consists of three parts: the function of the average cost of client servicing; the total minimum cost of servicing from a site, which is selected and included into the solution; the function of improving the cost of already serviced clients. In this comparison, simulations were presented, and two parameters were observed: the number of sites and the cost of client servicing. The new algorithm allowed to improve the solution in both of these parameters.https://doi.org/10.4467/2353737XCT.18.008.7959facility localisation problemant colony optimisationheuristic algorithm |
| spellingShingle | Schiff Krzysztof Ant Colony Optimisation Algorithm for the Facility Localisation Problem Technical Transactions facility localisation problem ant colony optimisation heuristic algorithm |
| title | Ant Colony Optimisation Algorithm for the Facility Localisation Problem |
| title_full | Ant Colony Optimisation Algorithm for the Facility Localisation Problem |
| title_fullStr | Ant Colony Optimisation Algorithm for the Facility Localisation Problem |
| title_full_unstemmed | Ant Colony Optimisation Algorithm for the Facility Localisation Problem |
| title_short | Ant Colony Optimisation Algorithm for the Facility Localisation Problem |
| title_sort | ant colony optimisation algorithm for the facility localisation problem |
| topic | facility localisation problem ant colony optimisation heuristic algorithm |
| url | https://doi.org/10.4467/2353737XCT.18.008.7959 |
| work_keys_str_mv | AT schiffkrzysztof antcolonyoptimisationalgorithmforthefacilitylocalisationproblem |