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Cyclic overlapping block coordinate search for optimizing building design

机译:循环重叠块坐标搜索以优化建筑设计

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In this article the most fundamental decomposition-based optimization method - block coordinate search, based on the sequential decomposition of problems in subproblems - and building performance simulation programs are used for reasoning about a building design, process at micro-urban scale and defining strategies for making the search more efficient. Cyclic overlapping block coordinate search is here considered in its double nature of optimization method and surrogate model (and metaphor) of a sequential design process. Heuristic indicators apt to support the design of search structures suited to that method are then developed from building-simulation-assisted computational experiments aimed to choose the form and position of a small building in a plot. Those indicators link the sharing of structure between subproblems ("commonality") to recursive recombination, measured as freshness of the search wake and novelty of the search moves, and can be of assistance in devising search structures suitable for being search efficiently. This is because they bring some memory of the search history to algorithms which otherwise would have not one. The aim of these indicators is to measure the relative effectiveness of alternatives for recursively decomposing problems so as to make searches more efficient than randomly structured ones. Implications of a possible use of these indicators in genetic algorithms are also highlighted. (C) 2016 Elsevier B.V. All rights reserved.
机译:在本文中,最基本的基于分解的优化方法-基于子问题中问题的顺序分解的块坐标搜索-以及建筑性能模拟程序,用于推理建筑设计,微观城市规模的过程以及确定策略。使搜索更加有效。这里考虑循环重叠块坐标搜索的双重性质是优化方法和顺序设计过程的替代模型(和隐喻)。然后从建筑物模拟辅助的计算实验中开发出适合于支持适合该方法的搜索结构设计的启发式指标,以选择小建筑物在地块中的形式和位置。这些指标将子问题之间的结构共享(“共性”)与递归重组联系起来,以搜索唤醒的新鲜度和搜索动作的新颖性来衡量,并且可以帮助设计适合于有效搜索的搜索结构。这是因为它们为算法带来了一些搜索历史记录,而这些算法本来就没有。这些指标的目的是测量递归分解问题的替代方法的相对有效性,以使搜索比随机结构的搜索更有效率。还着重指出了在遗传算法中可能使用这些指标的含义。 (C)2016 Elsevier B.V.保留所有权利。

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