2005
DOI: 10.1080/10286600500049946
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A methodology for defining building evacuation routes

Abstract: This paper concerns an innovative methodology aimed towards specifying the best evacuation plan in a given scenario - where a scenario is characterised by the enclosure geometry, the population’s capabilities and the population distribution within the building. The best evacuation plan is assumed to be the one which minimises the movement time of the last evacuee. The problem faced is an optimisation problem where the cost function to be minimised is the last evacuee’s movement time and the research space is… Show more

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Cited by 28 publications
(15 citation statements)
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References 9 publications
(6 reference statements)
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“…From the perspective of implementation purposes, these models can generally be divided into two categories, namely networkbased and area-based models. The network-based models, in which the spatial layout of a building is represented by a network based on the building's actual structure, can be used to evaluate the performance measures of evacuation plan [1][2][3][4]. The area-based models can be used to simulate the pedestrian dynamics in such closed areas as rooms, corridors and supermarkets.…”
Section: Introductionmentioning
confidence: 99%
“…From the perspective of implementation purposes, these models can generally be divided into two categories, namely networkbased and area-based models. The network-based models, in which the spatial layout of a building is represented by a network based on the building's actual structure, can be used to evaluate the performance measures of evacuation plan [1][2][3][4]. The area-based models can be used to simulate the pedestrian dynamics in such closed areas as rooms, corridors and supermarkets.…”
Section: Introductionmentioning
confidence: 99%
“…Since there is no analytical expression for h k (s), we cannot exclude the need to deal with a multi-peak function and the risk of reaching a local minimum, without being able to find the global minimum, is high [5]. To combat this issue and the fact that the search space is extremely large, Simulated Annealing (SA) has been chosen to solve the minimization problem.…”
Section: Minimize F S ð þ ð8þmentioning
confidence: 99%
“…As in Cepolina [5], the geometric temperature reduction function has been used: T k +1 =α ⋅T k where T k and T k+1 are the temperatures in two consecutive iterations of the algorithm. Typically, 0.7≤α ≤0.95.…”
Section: The Cooling Schedulementioning
confidence: 99%
“…Moreover, the dependence of the system cost from the number of boxes is implicit. Simulated Annealing (SA) seems suitable for approaching problems with these characteristics [1]. The main parameters of the SA algorithm are: the cooling schedule, and the neighbor search criterion.…”
Section: The Exploration Of the Search Spacementioning
confidence: 99%