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A modified Ant Colony System for the asset protection problem

Trachanatzi Dimitra, Rigakis Manousos, Marinaki Magdalini, Marinakis Ioannis

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URIhttp://purl.tuc.gr/dl/dias/8C6F7D56-1626-47D4-82B7-7FEC988ADDB7-
Identifierhttps://doi.org/10.1016/j.swevo.2022.101109-
Identifierhttps://www.sciencedirect.com/science/article/pii/S2210650222000797-
Languageen-
Extent12 pagesen
TitleA modified Ant Colony System for the asset protection problemen
CreatorTrachanatzi Dimitraen
CreatorΤραχανατζη Δημητραel
CreatorRigakis Manousosen
CreatorΡηγακης Μανουσοςel
CreatorMarinaki Magdalinien
CreatorΜαρινακη Μαγδαληνηel
CreatorMarinakis Ioannisen
CreatorΜαρινακης Ιωαννηςel
PublisherElsevieren
DescriptionThis 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 SummaryDuring 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 ItemPeer-Reviewed Journal Publicationen
Type of ItemΔημοσίευση σε Περιοδικό με Κριτέςel
Licensehttp://creativecommons.org/licenses/by/4.0/en
Date of Item2023-12-21-
Date of Publication2022-
SubjectAsset protection problemen
SubjectAnt colony optimizationen
SubjectSynchronizationen
SubjectVehicle routingen
Bibliographic CitationD. 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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