城市疏散分析的新机遇:Repast HPC中社会代理系统的超大规模模拟

K. Zia, A. Riener, K. Farrahi, A. Ferscha
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引用次数: 10

摘要

由于洪水或海啸、恐怖主义或核电站事故等自然力量引发的灾难性灾害,了解城市疏散系统的动态在过去几年中引起了巨大的兴趣。当离散事件模拟疏散模型在处理时间、空间和个体行为时变得过于复杂时,基于多智能体的模型显示出潜在的更有效的方法。本文介绍了大规模社会智能体的配置模型,结合最新的超级计算技术,可以对大城市(106 -108个智能体)级别的现实疏散模型进行模拟分析。基于Agent的人口统计和城市形态模型以及人口密度、移动模式、个人决策和Agent交互被实现到一个工具链中,最终生成Repast HPC代码,然后在2,048个节点的共享内存多处理器服务器(SGI Altix UV-1000)上执行。我们展示了如何基于昂贵但可行的模拟运行来评估不同的疏散策略——从而证明,一整类要求很高、非常复杂的模拟问题已经找到了令人信服的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A New Opportunity to Urban Evacuation Analysis: Very Large Scale Simulations of Social Agent Systems in Repast HPC
Due to catastrophic disasters induced by forces of nature like flooding or tsunamis, terrorism or nuclear power plant accidents, understanding the dynamics of urban evacuation systems has elicited massive interest over the past years. While discrete event simulations of evacuation models become prohibitively complex dealing with the time, space and individual behavior, multiagent based models have revealed to be a potentially more effective. This paper introduces models of configurations of social agents at a massive scale, which, together with the most recent supercomputing technology, allows for a simulation analysis of realistic evacuation models at the level of large cities (106 -108 agents). Agent based models of demographics and the morphology of cities together with population densities, mobility patterns, individual decision making, and agent interactions are implemented into a tool chain which ultimately generates Repast HPC code, which is then executed on a 2,048 node shared memory multiprocessor server (SGI Altix UV-1000). We demonstrate how different evacuation strategies can be assessed based on costly, yet feasible simulation runs - thus evidencing, that a whole class of demanding, very complex simulation problems has found a convincing solution.
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