A fuzzy maximum dynamic flow model for emergency building evacuation Present paper is devoted to the solution of the important task of the building evacuation, in particular, evacuation of the maximum number of suffered from the dangerous zone to the safe one within the given time horizon. The considered building model is represented by the transportation network with dynamic structure, as arc capacities and time parameters vary in time. Moreover, arcs of the network have weights that limit the upper bounds of the evacuees that can be arranged in the particular node. The fuzzy and ambiguous nature of the networkxe2x80x99s parameters leads to the problem statement in fuzzy conditions, in particular that allows to obtain more reliable results and deal with vague and incomplete input data. Numerical example is solved to represent the proposed method.

An Efficient Staged Evacuation Planning Algorithm Applied to MultiExit Buildings When the occupant density of buildings is large enough, evacuees are prone to congestion during emergency evacuation, which leads to the extension of the overall escape time. Especially for multiexit buildings, itxe2x80x99s a challenging problem to afford an effective evacuation plan. In this paper, a novel evacuation planning algorithm applied to multiexit buildings is proposed, which is based on an indoor route network model. Firstly, evacuees are grouped by their location proximity, then all groups are approximately equally classified into several evacuation zones, each of which has only one safe exit. After that, all evacuation groups in the same zone are sorted by their shortest path length, then the time window of each evacuation group occupying the safe exit is calculated in turn. In the case of congestion at the safe exit, the departure time of each evacuation group is delayed in its arrival order. The objectives of the proposed algorithm include minimizing the total evacuation time of all evacuees, the travel time of each evacuee, avoiding traffic congestion, balancing traffic loads among different exits, and achieving high computational efficiency. Case studies are conducted to examine the performance of our algorithm. The influences of group number, group size, evacuation speed on the total evacuation time are discussed on a singleexit network, and that of partitioning methods and evacuation density on the performance and applicability in different congestion levels are also discussed on a multiexit network. Results demonstrate that our algorithm has a higher efficiency and performs better for evacuations with a large occupant density.