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首页> 外文会议>International conference on omputational science and technology >Incorporating Cellular Automaton based Microscopic Pedestrian Simulation and Genetic Algorithm for Spatial Layout Design Optimization
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Incorporating Cellular Automaton based Microscopic Pedestrian Simulation and Genetic Algorithm for Spatial Layout Design Optimization

机译：基于蜂窝自动化的微观行人仿真和空间布局设计优化的遗传算法

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Autonomous spatial layout design had become the prominent applications for early planning process for a space arrangement. The available spatial layout design applications had focused on the structural and functional demands for a trendy, cultural influences and scalable spatial design. The previous research on the autonomous spatial layout design had proved that the Genetic Algorithm (GA) with full-fledged of operators are able to design an optimal spatial layout that is scalable for the space utilization. However, in these recent years, due to many occurrences of emergency incidents, the security assurance of the pedestrian to evacuate from the spatial layout during panic situation had become the main focus in designing a spatial layout. Hence, this research had proposed the pedestrian movement simulation using Cellular Automata (CA) with the Moore Neighborhood transition movement direction as the objective function for optimizing the GA operators based spatial layout design. The results have shown that the CA based pedestrian movement simulation was able to optimize the GA operators based spatial layout design in designing a feasible and scalable space arrangement with low-risk of pedestrian casualties.
机译：自动空间布局设计已成为空间安排早期规划过程的突出应用。可用的空间布局设计应用专注于对时尚，文化影响和可扩展的空间设计的结构和功能需求。先前关于自主空间布局设计的研究证明，具有全面运算符的遗传算法（GA）能够设计最佳的空间布局，可用于空间利用率。然而，在这近年来，由于许多发生的紧急事件发生，行人在恐慌情境期间从空间布局撤离的安全保障已成为设计空间布局的主要重点。因此，该研究提出了使用蜂窝自动机（CA）的行人运动模拟，其中摩尔邻域过渡运动方向作为优化基于GA操作员的空间布局设计的目标函数。结果表明，基于CA的行人运动模拟能够优化基于GA操作员的空间布局设计，设计具有低风险的可行和可扩展的空间布置。

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