Optimizing Housing Floor Layout for Cool Terraces: A Comparative Analysis Using Constrained Problem Formulation

Abstract

As urban densification increases, thermal stress in cities becomes a problem. The integration of climate-sensitive strategies into housing design has become a necessity. As a strategy, design of terraces, as thermally configured outdoor spaces can reduce solar radiation gain. Parametric modeling, one of the computational approaches, provides significant contributions to optimizing the integration of environmental analysis into the terrace design. Although some related studies have focused on optimizing urban mass organizations for thermal comfort and solar performance, none of them have addressed spatial organization of terraces in residential buildings. This study presents a computational housing model to investigate terrace allocation with respect to solar gain, including circulation and residential units. The interstitial spaces are considered "cool terraces", and the objective is to minimize the solar radiation on terraces by optimizing the location and size of the residential units using a genetic algorithm via the Galapagos plug-in, radial basis function optimization (RBFOpt), and covariance matrix adaptation with evolution strategy (CMA-ES) using Opossum plug-in. To provide feasible spatial organization, constraints are determined using the near feasibility threshold with the Optimus plug-in. Results showed that only CMA-ES discovered feasible spatial organization while improving the solar performance of cool terraces. When compared to the benchmark design scenarios, the optimized alternative performed 11-26% improvement in solar radiation minimization. The study discusses the challenges in identifying well-performing cool terrace solutions, the complexity of the problem, and the applicability of optimization algorithms.