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Institutional Repository [SANDBOX]
Technical University of Crete
Technical University of Crete
EN
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| URI | http://purl.tuc.gr/dl/dias/8C6F7D56-1626-47D4-82B7-7FEC988ADDB7 | - |
| Identifier | https://doi.org/10.1016/j.swevo.2022.101109 | - |
| Identifier | https://www.sciencedirect.com/science/article/pii/S2210650222000797 | - |
| Language | en | - |
| Extent | 12 pages | en |
| Title | A modified Ant Colony System for the asset protection problem | en |
| Creator | Trachanatzi Dimitra | en |
| Creator | Τραχανατζη Δημητρα | el |
| Creator | Rigakis Manousos | en |
| Creator | Ρηγακης Μανουσος | el |
| Creator | Marinaki Magdalini | en |
| Creator | Μαρινακη Μαγδαληνη | el |
| Creator | Marinakis Ioannis | en |
| Creator | Μαρινακης Ιωαννης | el |
| Publisher | Elsevier | en |
| Description | This research is co-financed by Greece and the European Union (European Social Fund- ESF) through the Operational Programme Human Resources Development, Education and Lifelong Learning in the context of the project “Strengthening Human Resources Research Potential via Doctorate Research” (MIS-5000432), implemented by the State Scholarships Foundation (IKY). | en |
| Content Summary | During an escaped wildfire in a populated area’s vicinity, protective tasks should be carried out to secure crucial community assets, e.g., bridges, hospitals, power stations, and communication towers. In a real-life scenario, an important asset may require the combined effort of different fire suppression resources, which should be dispatched and scheduled to act synchronously in protecting the respective asset. The present research addresses the solution of a challenging routing problem in emergency response, the Asset Protection Problem (APP), which incorporates selective characteristics in routing a heterogeneous vehicle fleet with complex temporal and spatial constraints, i.e., time windows and synchronization requirements. Notably, the Modified Ant Colony System (MACS) algorithm is proposed to obtain effective APP solutions within a time suitable for operational purposes. Based on the conducted experiments, MACS outperforms the previously published solution approaches in the solution of large-scale APP benchmark instances. Notably, MACS obtained superior solutions in 159 out of 240 large-scale instances, while 87 of them represent new best results, considering the solutions achieved by the commercial solver CPLEX with a ten-hour time limit. | en |
| Type of Item | Peer-Reviewed Journal Publication | en |
| Type of Item | Δημοσίευση σε Περιοδικό με Κριτές | el |
| License | http://creativecommons.org/licenses/by/4.0/ | en |
| Date of Item | 2023-12-21 | - |
| Date of Publication | 2022 | - |
| Subject | Asset protection problem | en |
| Subject | Ant colony optimization | en |
| Subject | Synchronization | en |
| Subject | Vehicle routing | en |
| Bibliographic Citation | D. Trachanatzi, M. Rigakis, M. Marinaki, and Y. Marinakis, “A modified Ant Colony System for the asset protection problem,” Swarm Evol. Comput., vol. 73, Aug. 2022, doi: 10.1016/j.swevo.2022.101109. | en |
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