In this paper, we propose a modified q-Dai–Yuan (q-DY) conjugate gradient algorithm based on q-gradient for solving unconstrained optimization problems. The q-gradient is calculated based on q-derivative that requires a dilation parameter q for controlling the balance between the local and global search. The strong global convergence of the algorithm is proved under standard Wolfe conditions, and numerical results show the efficiency of the proposed algorithm.