A MILP model and a heuristic algorithm for post-disaster connectivity problem with heterogeneous vehicles

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dc.authorid0000-0002-8115-3206
dc.authorid0000-0002-8758-2407
dc.contributor.authorTukenmez, Ilknur
dc.contributor.authorSarac, Tugba
dc.contributor.authorKaya, Onur
dc.date.accessioned2026-02-08T15:14:57Z
dc.date.available2026-02-08T15:14:57Z
dc.date.issued2024
dc.departmentBursa Teknik Üniversitesi
dc.description.abstractThroughout the response phase of the disaster, the speedy restoration of transportation by reconnecting the nodes where the connection is broken is absolutely critical for evacuating civilians, providing clear access to hospitals, and distributing aid. Following a disaster, some roads in a disaster area might be closed to transportation. In reality, some roads can be blocked due to debris, and some of roads can be blocked by collapsing. In this model, different types of road unblocking methods are included, and each road can only be opened to access by a vehicle suitable for that method. So, different types of vehicles may be needed to repair the roads depending on the type of damage. In addition, fast-built bridges built both on land and over water are also used if necessary following a disaster. In problems of this nature, it is essential to restore the roads to enable the complete connectivity of the network such that all nodes can be reached by one another. In addition, it is also critical for the speedy reach of critical nodes, such as hospitals, and emergency disaster centers. This study aims to reduce the maximum time for connection and minimize the total time in which to reach critical nodes. For this purpose, we developed a bi-objective mathematical model that considers the multiple vehicle types that can repair different types of damages. Since the problem is NP-hard, two heuristic methods were developed, and the numerical results were presented. It has been observed that the local search algorithm gives better results than the hybrid algorithm. Additionally, different scenario data was produced. Numbers of unconnected components from 3 to 10 are solved with heuristic algorithms for test data containing 80 and 250 nodes, and real-life data containing 223 nodes and 391 edges are solved with heuristic algorithms for the number of unconnected components 6, 9, 12, and 15.
dc.identifier.doi10.1007/s10732-024-09531-4
dc.identifier.endpage396
dc.identifier.issn1381-1231
dc.identifier.issn1572-9397
dc.identifier.issue5-6
dc.identifier.scopus2-s2.0-85198997186
dc.identifier.scopusqualityQ1
dc.identifier.startpage359
dc.identifier.urihttps://doi.org/10.1007/s10732-024-09531-4
dc.identifier.urihttps://hdl.handle.net/20.500.12885/5525
dc.identifier.volume30
dc.identifier.wosWOS:001271500700001
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherSpringer
dc.relation.ispartofJournal of Heuristics
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzWOS_KA_20260207
dc.subjectConnectivity problem
dc.subjectArc routing
dc.subjectLocal search algorithm
dc.subjectHybrid algorithm
dc.subjectDisaster management
dc.titleA MILP model and a heuristic algorithm for post-disaster connectivity problem with heterogeneous vehicles
dc.typeArticle

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