Ιδρυματικό Αποθετήριο
Πολυτεχνείο Κρήτης
Πολυτεχνείο Κρήτης
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| URI | http://purl.tuc.gr/dl/dias/8C6F7D56-1626-47D4-82B7-7FEC988ADDB7 | - |
| Αναγνωριστικό | https://doi.org/10.1016/j.swevo.2022.101109 | - |
| Αναγνωριστικό | https://www.sciencedirect.com/science/article/pii/S2210650222000797 | - |
| Γλώσσα | en | - |
| Μέγεθος | 12 pages | en |
| Τίτλος | A modified Ant Colony System for the asset protection problem | en |
| Δημιουργός | Trachanatzi Dimitra | en |
| Δημιουργός | Τραχανατζη Δημητρα | el |
| Δημιουργός | Rigakis Manousos | en |
| Δημιουργός | Ρηγακης Μανουσος | el |
| Δημιουργός | Marinaki Magdalini | en |
| Δημιουργός | Μαρινακη Μαγδαληνη | el |
| Δημιουργός | Marinakis Ioannis | en |
| Δημιουργός | Μαρινακης Ιωαννης | el |
| Εκδότης | Elsevier | en |
| Περιγραφή | 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 |
| Περίληψη | 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 |
| Τύπος | Peer-Reviewed Journal Publication | en |
| Τύπος | Δημοσίευση σε Περιοδικό με Κριτές | el |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
| Ημερομηνία | 2023-12-21 | - |
| Ημερομηνία Δημοσίευσης | 2022 | - |
| Θεματική Κατηγορία | Asset protection problem | en |
| Θεματική Κατηγορία | Ant colony optimization | en |
| Θεματική Κατηγορία | Synchronization | en |
| Θεματική Κατηγορία | Vehicle routing | en |
| Βιβλιογραφική Αναφορά | 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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