Article | The 29th Annual Workshop of the Swedish Artificial Intelligence Society (SAIS), 2–3 June 2016, Malmö, Sweden | Towards Evacuation Planning of Groups with Genetic Algorithms Linköping University Electronic Press Conference Proceedings
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Title:
Towards Evacuation Planning of Groups with Genetic Algorithms
Author:
Bjørnar Hansen: Department of ICT, University of Agder, Grimstad, Norway Leonard Loland: Department of ICT, University of Agder, Grimstad, Norway Morten Goodwin: Department of ICT, University of Agder, Grimstad, Norway Ole-Christoffer Granmo: Department of ICT, University of Agder, Grimstad, Norway
Download:
Full text (pdf)
Year:
2016
Conference:
The 29th Annual Workshop of the Swedish Artificial Intelligence Society (SAIS), 2–3 June 2016, Malmö, Sweden
Issue:
129
Article no.:
003
Pages:
8
No. of pages:
23-30
Publication type:
Abstract and Fulltext
Published:
2016-06-20
ISBN:
978-91-7685-720-5
Series:
Linköping Electronic Conference Proceedings
ISSN (print):
1650-3686
ISSN (online):
1650-3740
Publisher:
Linköping University Electronic Press, Linköpings universitet

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In crisis situations on board ships, it is of utmost importance to have the passengers safely evacuate to the lifeboats in an efficient manner. Existing methods such as marked escape routes and maps are not optimal as pre-planned escape routes may become heavily congested by passengers. Further, the closest lifeboat is not always feasible as lifeboat capacity can be exceeded. Also considering that some evacuees are strongly affiliated, such as families, and that they prefer to evacuate together as a group, it becomes a difficult problem to solve. This paper models the area to be evacuated as a time-expanded graph with hazard severities as probabilities of survivability for each node. The presented approach applies a multi-objective genetic algorithm with multiple fitness functions to maximize the over all survivability. Finally, the proposed method picks the best evacuation plan from a pool of potential solutions returned by the genetic algorithm. The solution generates better routing plans than comparable methods, specially in situations where grouping and congestions are considered. In essence this is an essential step towards automatic planning of evacuations which in turn contributes to smoother evacuations of crises situations and saving lives.

Keywords: artificial intelligence

The 29th Annual Workshop of the Swedish Artificial Intelligence Society (SAIS), 2–3 June 2016, Malmö, Sweden

Author:
Bjørnar Hansen, Leonard Loland, Morten Goodwin, Ole-Christoffer Granmo
Title:
Towards Evacuation Planning of Groups with Genetic Algorithms
References:

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The 29th Annual Workshop of the Swedish Artificial Intelligence Society (SAIS), 2–3 June 2016, Malmö, Sweden

Author:
Bjørnar Hansen, Leonard Loland, Morten Goodwin, Ole-Christoffer Granmo
Title:
Towards Evacuation Planning of Groups with Genetic Algorithms
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