The gannet optimization algorithm (GOA) is a newly proposed swarm intelligence optimization algorithm, and the algorithm is inspired by the predatory habit of the natural creature gannet, which has a strong exploration-exploitation performance. In this paper, we optimize the GOA by using the core concept of an evolutionary matrix in the QUasi-affine TRansformation Evolutionary (QUATRE) algorithm to form the Gannet Optimization Algorithm with QUasi-affine TRansformation Evolutionary (QTGOA). The performance of the QTGOA is compared with five classical optimization algorithms using the CEC2013 test set, and the performance of the QTGOA is proved to be competitive.