Layout planning is a process of sizing and placing rooms in a building or house, while attempting to optimize various criteria. Often there are conflicting criteria, such as functional requirements, construction cost, minimizing the distance between related activities, and meeting the area requirements for these activities. The process of layout planning has mostly been done by hand, with a handful of attempts to automate the process. This research explores several new techniques for automating the layout planning process using evolutionary computation. Several multi-objective approaches are used to evaluate and compare fitness. In particular, Pareto and normalized sum of ranks scoring are compared. The sum of ranks approach has the advantage of permitting an overall balance of objectives, and discouraging outlier solutions common with Pareto ranking. The evolutionary representation and requirements specification used provide great flexibility in problem scope and depth and is worthy of considering in future layout and design attempts. Many of the resulting plans look reasonable even when compared to a professional floor plan. Additionally polygonal and multi-floor buildings were also generated. |
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