Ant Colony-Dijkstra’s Algorithm for Evacuation Preparedness in High Rise Buildings

Sabri, Nor Amalina Mohd; Basari, Abd Samad Hasan; Hussin, Burairah; Samah, Khyrina Airin Fariza Abu; Wahab, Yuseni Ab

doi:10.1007/978-3-319-24584-3_46

Cited by 1 publication

(1 citation statement)

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“…Ant colony optimization (ACO) is a strong category of metaheuristic algorithms based on the real ants behaviour to forage food (Maniezzo et al, 1991). ACO algorithms have promising results for TSP (Dorigo et al, 2010) and its generalized form Vehicle Routing Problems (VRP) (Gambardella et al, 1999) and more recently it is being used for optimizing evacuation routes inside buildings (Sabri et al, 2016). SRP's accuracy relies heavily on having a detailed underlying route network that would integrate the outdoor road network with the indoor graph.…”

Section: Search and Rescue In Complex Indoor Environmentsmentioning

confidence: 99%

Facilitating the 3d Indoor Search and Rescue Problem: An Overview of the Problem and an Ant Colony Solution Approach

Tashakkori¹,

Rajabifard²,

Kalantari³

2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Search and rescue procedures for indoor environments are quite complicated due to the fact that much of the indoor information is unavailable to rescuers before physical entrance to the incident scene. Thus, decision making regarding the number of crew required and the way they should be dispatched in the building considering the various access points and complexities in the buildings in order to cover the search area in minimum time is dependent on prior knowledge and experience of the emergency commanders. Hence, this paper introduces the Search and Rescue Problem (SRP) which aims at finding best search and rescue routes that minimize the overall search time in the buildings. 3D BIM-oriented indoor GIS is integrated in the indoor route graph to find accurate routes based on the building geometric and semantic information. An Ant Colony Based Algorithm is presented that finds the number of first responders required and their individual routes to search all rooms and points of interest inside the building to minimize the overall time spent by all rescuers inside the disaster area. The evaluation of the proposed model for a case study building shows a significant improve in search and rescue time which will lead to a higher chance of saving lives and less exposure of emergency crew to danger.

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Section: Search and Rescue In Complex Indoor Environmentsmentioning

confidence: 99%