LAUSR

QUasi-Affine TRansformation Evolutionary (QUATRE) algorithm generalized differential evolution (DE) algorithm to matrix form QUATRE was originally designed for a continuous search space, but many practical applications are binary optimization problems Therefore, we designed a novel binary version of QUATRE The proposed binary algorithm is implemented using two different approaches In the first approach, the new individuals produced by mutation and crossover operation are binarized In the second approach, binarization is done after mutation, then cross operation with other individuals is performed Transfer functions are critical to binarization, so four families of transfer functions are introduced for the proposed algorithm Then, the analysis is performed and an improved transfer function is proposed Furthermore, in order to balance exploration and exploitation, a new liner increment scale factor is proposed Experiments on 23 benchmark functions show that the proposed two approaches are superior to state-of-the-art algorithms Moreover, we applied it for dimensionality reduction of hyperspectral image (HSI) in order to test the ability of the proposed algorithm to solve practical problems The experimental results on HSI imply that the proposed methods are better than Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA)