Nature-Inspired Optimization: Optimizing Distance of Emergency Response Wagons en Route to Railway Crossing Accident Location

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dc.contributor.authorAgbehadji I.E.
dc.contributor.authorMillham R.C.
dc.contributor.authorFong S.J.
dc.contributor.authorAgbehadzi R.K.
dc.contributor.editorTallon-Ballesteros A.J.; Cortes-Ancos E.; Lopez-Garcia D.A.
dc.date.accessioned2025-03-06T18:11:43Z
dc.date.accessioned2025-03-06T18:58:55Z
dc.date.issued2024
dc.description.abstractThe problem is that when an accident occurs at a railway crossing, emergency response wagons are unable to get to the accident location on time. In this study, we consider the location of emergency response wagons and railway accident location and apply a nature-inspired search strategy as a solution to compute the optimal distance for an emergency response wagon such that when an accident occurs the expected time to reach the accident location can be minimized. The outcome suggests the ideal objective function, haversine method, because it produced the optimal minimal distance of 994, 691.90km with a computational time of 1.05s for KSA over comparative algorithms namely BAT and (Ant Colony Optimization) ACO. � 2024 The authors and IOS Press.
dc.identifier.doi10.3233/FAIA231254
dc.identifier.isbn978-164368480-2
dc.identifier.issn9226389
dc.identifier.urihttp://162.250.124.58:4000/handle/123456789/348
dc.language.isoen
dc.publisherIOS Press BV
dc.sourceFrontiers in Artificial Intelligence and Applications
dc.subjectemergency response
dc.subjectNature-inspired optimization
dc.subjectrailway crossing
dc.titleNature-Inspired Optimization: Optimizing Distance of Emergency Response Wagons en Route to Railway Crossing Accident Location
dc.typeOther
oaire.citation.conferenceDate17 November 2023 through 20 November 2023
oaire.citation.conferencePlaceHybrid, Macau

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