<p>Various conflicting responses are frequently involved in optimization problems that arise in various scenarios. An approach to determining the ideal air conditioning load of a typical residential apartment is presented in this paper: the Taguchi based GRA optimization approach. The building energy simulation was carried out using the HAP 4.90 software and AutoCAD software to model this residential apartment. The process of optimizing the air conditioning load comprised the selection of eight factors: the cooling coil supply temperature (F), the infiltration flow rate (G), the bypass factor (H) of the air conditioning equipment at three levels, the overall heat transfer coefficient of the wall (A), the thickness of the roof insulation (B), the roof insulation material (C), the heat transfer coefficient of the window glass (D), and the window to wall ratio (E). For the experimental tests, an orthogonal L27 arrangement is employed. The residential apartment’s heating and cooling loads are computed for each trial. The S/N ratios of all three response variables produce a decision matrix, which is then used to convert the multiple response problem into a single response problem using the Grey Relational Analysis (GRA). Then, using the statistical program Minitab 17, one can calculate the signal to noise ratios for different factors by choosing the smaller is better option. After examining the response table for Taguchi tests, the ideal levels for each of the eight factors are established for each response variable independently. The analysis of variance method was also used to identify the main factors that significantly influenced the outcomes by calculating the percentage contributions of each of the eight factors. The residential flat’s wall material has the biggest impact, contributing 82.10%, and the results indicated that A1B3C2D1E1F2G1H1 is the most effective set of all eight factors.</p>