Abstract
This paper proposes a first step towards multidisciplinary design of building spatial designs. Two criteria, total surface area (i.e. energy performance) and compliance (i.e. structural performance), are combined in a multicriteria optimisation framework. A new way of representing building spatial designs in a mixed integer parameter space is used within this framework. Two state-of-the-art algorithms, namely NSGA-II and SMS-EMOA, are used and compared to compute Pareto front approximations for problems of different size. Moreover, the paper discusses domain specific search operators, which are compared to generic operators, and techniques to handle constraints within the mutation. The results give first insights into the trade-off between energy and structural performance and the scalability of the approach.
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Acknowledgments
The authors gratefully acknowledge the financing of this project by the Dutch STW via project 13596 (Excellent Buildings via Forefront MDO, Lowest Energy Use, Optimal Spatial and Structural Performance).
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van der Blom, K., Boonstra, S., Hofmeyer, H., Emmerich, M.T.M. (2016). Multicriteria Building Spatial Design with Mixed Integer Evolutionary Algorithms. In: Handl, J., Hart, E., Lewis, P., López-Ibáñez, M., Ochoa, G., Paechter, B. (eds) Parallel Problem Solving from Nature – PPSN XIV. PPSN 2016. Lecture Notes in Computer Science(), vol 9921. Springer, Cham. https://doi.org/10.1007/978-3-319-45823-6_42
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DOI: https://doi.org/10.1007/978-3-319-45823-6_42
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