Process / pipelineSimulation / optimization
多目标元胞自动机 — 以多个相互竞争的目标为指导的空间模拟
多目标元胞自动机（Multi-Objective Cellular Automata, MOCA）将元胞自动机的自下而上的空间动力学与多目标优化相结合，以同时追求相互竞争的目标——例如，在最小化生态系统损失的同时最大化城市紧凑度。每个网格元胞根据转换规则更新其状态，这些规则经过校准或引导，以在两个或多个目标之间实现帕累托最优权衡，这使得该方法广泛应用于土地利用变化模拟、城市增长建模以及在冲突需求下的空间规划。
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来源
- Liu, X., Liang, X., Li, X., Xu, X., Ou, J., Chen, Y., Li, S., Wang, S., Pei, F. (2017). A future land use simulation model (FLUS) for simulating multiple land use scenarios by coupling human and natural effects. Landscape and Urban Planning, 168, 94-116. DOI: 10.1016/j.landurbplan.2017.09.019 ↗
- Jantz, C. A., Goetz, S. J., Shelley, M. K. (2004). Using the SLEUTH urban growth model to simulate the impacts of future policy scenarios on urban land use in the Baltimore-Washington metropolitan area. Environment and Planning B: Planning and Design, 31(2), 251-271. DOI: 10.1068/b2983 ↗
如何引用本页
ScholarGate. (2026, June 3). Multi-Objective Cellular Automata — Simulation-based spatial optimization with multiple competing objectives. ScholarGate. https://scholargate.app/zh/simulation/multi-objective-cellular-automata
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