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A surrogate-assisted optimization framework for microclimate-sensitive urban design practice

机译：用于小型敏感城市设计实践的代理辅助优化框架

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Simulations can often benefit microclimate-sensitive urban design by offering insightful abstractions of stochastic urban system behaviors, yet many of them are difficult to use and generally consume significant computational resources. We adapt an advanced surrogate-assisted evolutionary optimization algorithm instead of other empirical multi-objective evolutionary algorithms commonly used to search for optimal design alternatives to confront the challenge. Moreover, a parametric design module is hybridized with this surrogate-assisted evolutionary optimization algorithm to create a working scheme for mathematically modeling microclimatesensitive urban design problems. This seven-step scheme is tested using a hypothetical case, a spatial planning problem in a residential block, to search for design proposals that maximize project development profits and facilitate the needed creation of a comfortable wind environment. Moreover, by utilizing three optimization solvers, we obtained a near-optimal site plan with a wind velocity ratio of 0.36, a wind velocity Gini index of 0.31, and a gross profit of 4.05 ? 108 RMB. Also, the case study results show that the proposed optimization framework, which consists of a global surrogate (additive Gaussian process model) and a local surrogate (gradient boosted regression trees model), converges faster and provides better optimal solutions to a highdimensional design problem compared to the algorithm which only uses a single surrogate. Built with a flexible structure, we believe the proposed framework can address the emerging demands for a wide range of microclimate-sensitive design tasks, especially those with costly simulations and small experimental datasets.
机译：模拟通常可以通过随机提供的城镇体系的行为有见地的抽象受益气候敏感的城市设计，但其中不少是难以使用和一般消耗显著的计算资源。我们采用先进的替代辅助进化优化算法，而不是常用的搜索优化设计方案，以应对面临的挑战等经验多目标进化算法。此外，参数化设计模块与该代孕辅助进化优化算法杂交创造数学建模microclimatesensitive城市设计问题的工作方案。这七步方案是利用一个假设的情况下，在一个居民区的空间规划问题，寻找设计方案，最大限度地提高项目的开发利润和方便舒适的风环境的需要建立测试。此外，通过使用三个优化求解，我们获得了0.36的风速比，0.31的风速基尼指数，以及毛利4.05接近最佳位置的计划吗？ 108元。此外，案例研究结果表明相比，所提出的优化框架，其中包括一个全球性的替代（加性高斯过程模型）和局部替代的（梯度提振回归树模型），收敛速度更快，提供了更好的优化解决方案，以高维设计问题到仅使用一个单一的替代算法。建有一个灵活的结构，我们认为拟议的框架可满足对大范围的气候敏感的设计任务，尤其是那些昂贵的模拟和小型实验数据集的新需求。

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