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Optimizing Architectural Layout Design via Mixed Integer Programming

机译:通过混合整数编程优化建筑布局设计

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摘要

For many decades, solving the optimal architectural layout design is unattainable for thernreasonable problem sizes. Architects have to settle for acceptable layouts instead of the favourable optimal solution. With today technologies, various optimization techniques have been used to alleviate the optimal search according to diversified goals. This paper formulates the optimal architectural layout design as the multiobjective mixed integer programming model solved by the MIP solver. The main idea is to capture functional constraints, dimensional constraints and the objective function using only linear formulae with binary variables. Functional constraints are the connectivities, the unused grid cells, the fixed room location, the boundary and the fixed border location while dimension constraints are the non-intersecting, the overlapping, the length and the ratio constraints. The objective function is designed to minimize the absolute distance among rooms and maximize room spaces. Due to the nonlinearity of area computation, the linear approximation of width and height constraints have been utilized. Architects can control these different objectives within the model. By specifying the rigid restriction and the time limits, the problem can be solved within a reasonable amount of time.
机译:数十年来,对于合理的问题规模,解决最佳的建筑布局设计是无法实现的。建筑师必须选择可接受的布局,而不是采用最佳的最佳解决方案。利用当今的技术,已经根据多样化的目标使用了各种优化技术来减轻最优搜索。本文将最佳的建筑布局设计公式化为MIP求解器求解的多目标混合整数规划模型。主要思想是仅使用带有二进制变量的线性公式来捕获功能约束,尺寸约束和目标函数。功能性约束是连通性,未使用的网格单元,固定的房间位置,边界和固定的边界位置,而尺寸约束是不相交,重叠,长度和比率约束。目标函数旨在最小化房间之间的绝对距离并最大化房间空间。由于面积计算的非线性,已利用宽度和高度约束的线性近似。架构师可以控制模型中的这些不同目标。通过指定严格的限制和时间限制,可以在合理的时间内解决问题。

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