In order to solve the problem that the accuracy of the spectral reflectance reconstruction based on RGB three-channel values is not ideal, an optimized spectral reflectance reconstruction algorithm based on RGB three-channel information was proposed. Firstly we coded to generate individuals with multiple illuminants selected randomly, and RGB three-channel values were used to predict CIE XYZ values under multi-illuminant by polynomial regression algorithm, and the pseudo-inverse method was used to reconstruct the spectral reflectance. Then the reconstruction accuracy of the sample was taken as the fitness evaluation value of the individual, and the individuals were selected, crossed, and mutated based on the principle of survival of the fittest. Finally, the combination of multiple illuminants which were suitable for spectral reconstruction of color samples were obtained, and then used to reconstruct the spectral of color samples. Munsell color set was used as training samples, RC24 chart and SG140 chart were used as test samples, and 8 standard illuminants and 82 LED light sources were used as experimental light sources. The proposed method was used to select the optimal combination from the 90 illumination sources and reconstruct the spectral reflectance of the test samples, and compared with the method based on multi-illuminant selected by exhaustive method proposed by Zhang and the pseudo-inverse method under A light source. The experimental results show that the spectral reflectance reconstruction accuracy is improved as the number of light sources increases, and the increase achieves the most when the number of light sources reach to 3. Among the three reconstruction methods, the average color difference and average root mean square error of the proposed method are 0.332 4 and 0.002 9 respectively for the RC24 chart, while the average color difference of the Zhang and pseudo-inverse methods are 0.429 3 and 3.266 respectively, and their average root mean square error are 0.029 7 and 0.004 8. For the SG140 chart, the average color difference and average root mean square error of the proposed method are 0.486 2 and 0.007 3 respectively, while the average color differences of the Zhang and pseudo-inverse methods are 0.544 8 and 3.821 9 respectively, and the average root mean errors are 0.035 6 and 0.013 3 respectively. The results show that the spectral reconstruction accuracy obtained under multi-illuminant is obviously superior to the one obtained under a single light source, and the results of the multi-illuminant selection method based on genetic algorithm is better than those of the exhaustive method. The genetic algorithm can automatically find the optimal illuminant combination according to the color samples, so as to reconstruct the spectral reflectance of the sample based on the optimal combination improving the accuracy of spectral reconstruction.