Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/18137
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dc.contributor.authorHassan, FH-
dc.contributor.authorSwift, S-
dc.contributor.authorTucker, A-
dc.date.accessioned2019-05-19T06:46:32Z-
dc.date.available2014-10-15-
dc.date.available2019-05-19T06:46:32Z-
dc.date.issued2014-
dc.identifier.citationJournal of Algorithmic Optimization, 2014, 2 (4), pp. 86 - 104 (19)en_US
dc.identifier.issn2312-7759-
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/18137-
dc.description.abstractA spatial layout design must consider not only ease of movement, but also safety in a panic situation, such as an emergency evacuation in a theatre, stadium or hospital. Using pedestrian simulation statistics, the activity of crowds can be used to study the consequences of different spatial layouts. A cellular automaton has been proposed to model pedestrian simulation so that pedestrian flows can be explored at a microscopic level. We examined four-way pedestrian flow statistics generated from feasible seating layout solutions using heuristic search techniques (hill climbing, simulated annealing and genetic algorithm style operators). The technique has shown promising results in identifying useful characteristics of spatial layout and sources of the pedestrian clogging phenomenon.en_US
dc.format.extent86 - 104 (19)-
dc.language.isoenen_US
dc.publisherWorld Academic Publishingen_US
dc.subjectcellular automataen_US
dc.subjectsimulated annealingen_US
dc.subjecthill climbingen_US
dc.subjectgenetic algorithmen_US
dc.subjectpedestrian simulation statisticsen_US
dc.subjectspatial layouten_US
dc.titleUsing Heuristic Search with Pedestrian Simulation Statistics to Find Feasible Spatial Layout Design Elementsen_US
dc.typeArticleen_US
dc.relation.isPartOfJournal of Algorithmic Optimization-
pubs.issue4-
pubs.publication-statusPublished online-
pubs.volume2-
Appears in Collections:Dept of Computer Science Research Papers

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