The Safest Escape problem

Opasanon, Sathaporn; Miller-Hooks, Elise

doi:10.1057/jors.2008.122

Cited by 21 publications

(17 citation statements)

References 28 publications

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“…how many people can walk abreast without impeding each other. Network Flow Graphs are often used to model road traffic in emergencies [14,15] and as a basis for dynamic evacuation planning [10,11,12]. In this research, we use the flow capacity constraint to determine how long it takes for an entire group of occupants to completely traverse the edge, analogous to calculating the amount of time it takes to transfer a given amount of data across a network link of limited bandwidth…”

Section: Network Flow Graphmentioning

confidence: 99%

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Problem Decomposition for Evacuation Simulation Using Network Flow

Murphy

Brown

Sreenan

2012

2012 IEEE/ACM 16th International Symposium on Distributed Simulation and Real Time Applications

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Abstract. Simulation of building evacuations can be a powerful tool for predicting evacuation outcomes, but for this prediction to be useful it must be produced in a timely manner. The building evacuation outcomes are dependent on the movement decisions of the occupants, but simulating all possible combinations of occupant decisions is infeasible. Our contribution is a novel technique using building structure knowledge in the form of a Network Flow Graph to determine where and when occupants might interact with one another. We decompose the problem into non-interacting groups, to be simulated separately, which leads to a significant simulation workload reduction.Keywords: evacuation monitoring, multi-agent simulation, distributed simulation, network flow graph, problem decomposition IntroductionSimulation of building evacuation during emergencies is a powerful tool for evaluating building safety and prediction of evacuation outcomes [1]. Simulating the movement of evacuating pedestrians can provide useful information to building designers and to fire safety officials, including evacuation time estimates and locations at risk of traffic congestion or evacuee injury [1][2][3][4][5][6][7]. We make use of a 2D vector-space pedestrian simulator to simulate the individual movements of pedestrians in the building. This simulator provides a realistic model of pedestrian movement but is computationally intensive compared to simpler models such as Cellular Automata [2,4,10] or Graph-based simulations [5]. The usefulness of any prediction information is contingent on both the timeliness and the accuracy of the simulation that generated it. Since a real evacuation involves autonomous human actors and uncertain hazard spread, to ensure that the simulations cover likely scenarios we must run many different scenarios. The more we can reduce the simulation time, the more scenarios we can consider, and the more useful the results will be. In this paper, we investigate the problem of how to cover a wide range of scenarios without an excessive increase in computation time.We assume that clusters of individuals in an evacuation will behave as a group, and once they have formed a group all members will follow the same route out of the building. We reduce the amount of simulation by limiting our attention to the most likely routes for each initial group. However, different groups may meet during the evacuation and cause congestion, and may form into larger groups to continue the evacuation. Since congestion slows down the evacuation, and puts the participants at risk, we must investigate the interaction of the different groups. Even for small numbers of likely routes, this group interaction quickly produces an excessively large simulation space. We reduce the complexity of the problem by quickly generating possible group interactions using Network-Flow Graph analysis, identifying groups and routes which do not interact, distributing the simulation of those local scenarios to different processors, and then combining the results to pro...

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Section: Network Flow Graphmentioning

confidence: 99%

“…This evacuation planner accounts for the location of hazards and produces evacuation routes that minimize evacuation time and exposure to the hazard. Alternative route generation schemes could be used, such as dynamic flow-based planners [10][11][12] or exploiting day-to-day sensor data to discover common exit routes.…”

Section: Route Allocationmentioning

confidence: 99%

Problem Decomposition for Evacuation Simulation Using Network Flow

Murphy

Brown

Sreenan

2012

2012 IEEE/ACM 16th International Symposium on Distributed Simulation and Real Time Applications

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“…Alternative objectives that consider these and other issues of equity that arise in solutions for the evacuation problem have been proposed in the literature (e.g. [19,27]). Regardless of the objective that is chosen for the determination of the optimal instructions, the issue of shared information arises if instructions are to be provided by changeable message signs or comparable technologies that inform more than one person at a time.…”

Section: Conclusion and Future Researchmentioning

confidence: 99%

The building evacuation problem with shared information

Chen

Miller-Hooks

2008

Naval Research Logistics

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Abstract:In this article, the Building Evacuation Problem with Shared Information (BEPSI) is formulated as a mixed integer linear program, where the objective is to determine the set of routes along which to send evacuees (supply) from multiple locations throughout a building (sources) to the exits (sinks) such that the total time until all evacuees reach the exits is minimized. The formulation explicitly incorporates the constraints of shared information in providing online instructions to evacuees, ensuring that evacuees departing from an intermediate or source location at a mutual point in time receive common instructions. Arc travel time and capacity, as well as supply at the nodes, are permitted to vary with time and capacity is assumed to be recaptured over time. The BEPSI is shown to be NP-hard. An exact technique based on Benders decomposition is proposed for its solution. Computational results from numerical experiments on a real-world network representing a four-story building are given. Results of experiments employing Benders cuts generated in solving a given problem instance as initial cuts in addressing an updated problem instance are also provided.

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“…Also the field of evacuation planning has seen rising interest in the application of operations research models to help the decision maker assessing a critical situation, and making the right choices to potentially safe lives, see, e.g., [OMH09,LKN11]. For general overviews, we refer to [HT01,AG06].…”

Section: Introductionmentioning

confidence: 99%

Robust flows with losses and improvability in evacuation planning

Goerigk

Ndiaye

2016

EURO Journal on Computational Optimization

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We consider a network flow problem, where the outgoing flow is reduced by a certain percentage in each node. Given a maximum amount of flow that can leave the source node, the aim is to find a solution that maximizes the amount of flow which arrives at the sink.Starting from this basic model, we include two new, additional aspects: On the one hand, we are able to reduce the loss at some of the nodes; on the other hand, the exact loss values are not known, but may come from a discrete uncertainty set of exponential size.Applications for problems of this type can be found in evacuation planning, where one would like to improve the safety of nodes such that the number of evacuees reaching safety is maximized.We formulate the resulting robust flow problem with losses and improvability as a mixed-integer program for finitely many scenarios, and present an iterative scenario-generation procedure that avoids the inclusion of all scenarios from the beginning. In a computational study using both randomly generated instance and realistic data based on the city of Nice, France, we compare our solution algorithms.

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The Safest Escape problem

Cited by 21 publications

References 28 publications

Problem Decomposition for Evacuation Simulation Using Network Flow

Problem Decomposition for Evacuation Simulation Using Network Flow

The building evacuation problem with shared information

Robust flows with losses and improvability in evacuation planning

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