Optimization of Indoor Space Layout Using Chameleon Swarm Algorithm

An indoor space layout is one of the significances in Geographic Information Science (GIS) application, due it develops the efficient indoor spatial patterns which enhance the efficiency as well as behavior of the human. However, some research examining the indoor room optimal allocation has been reported. To address this problem, this research proposes the integrative approach of the Chameleon Swarm Algorithm (CSA) for the indoor space layout. This approach involves the two approaches like indoor room allocation optimization as well as indoor connective map design. The objective of an optimization process according to the parametric performance simulation utilized in this research can efficiently assists the building designers in making energy-saving design decisions in the primary stage, permitting the designers to have the condition to pursue in an original design operation process. The experimental results shows that the proposed method attains better results and it is validated through various error metrices like Mean Absolute Error (MAE), Mean Squared Eror (MSE), and R-Squared (R2) and it achieves the values of about 0.453, 0.045 and 0.756 in cooling demand.