The cockpit is a compact space comprised of various light-emitting devices. The light from different devices interferes and overlaps on the target surface. The light distribution requirements of different target surfaces are different. A suitable decision-making process is required to simultaneously meet the requirements of multiple target surfaces. A GPR-NSGA-II framework was proposed in the present study and a corresponding Gaussian process regression prediction model was established to predict and optimize multiple optical quality parameters in the cockpit. The luminous flux and beam angle of the typical luminaires were selected as controlled input parameters in a model case. The average illumination of targets that need lighting were set as constraints, and uniformity of illuminance of these surfaces and vertical illumination (direct light) of the eye position were set as the variables. An orthogonal experiment was conducted using the lighting model and a dataset was generated to validate the proposed framework. The results demonstrate that the solution set of luminescence parameters in cockpit illumination can be specified by GPR-NSGA-II framework.