Black-Box Optimization of Lighting Simulation in Architectural Design

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In M.-A. Cardin, D. Krob, P. C. Lui, Y. H. Tan, and K. Wood (Eds.), Complex Systems Design & Management Asia (2015), 27–39, Springer

Alberto CostaGiacomo NanniciniThomas Schroepfer, and Thomas Wortmann

This paper deals with an application of optimization in architectural design. Formally, we consider the problem of optimizing a function that can only be evaluated through an expensive oracle. We assume that the analytical expression of the function is unknown and first-order information is not available. This situation frequently occurs when each function evaluation relies on the output of a complex and time-consuming simulation. In the literature, this is called a black-box optimization problem with costly evaluation. This paper presents a black-box problem from architectural design: we aim to find the values of the design variables that yield optimal lighting conditions inside a building. The building facade is described as a parametric model whose parameters are the design variables. We tackle this problem by adapting the Radial Basis Function (RBF) method originally proposed by Gutmann (2001). Experiments indicate that our open-source implementation is competitive with commercial software for black-box optimization, and that it can be a valuable decision-support tool for complex problems requiring time-consuming simulations. The usefulness of this approach goes beyond the specific application in architectural design.

2017-10-23T14:01:45+00:00 Publications|