This paper solves the shortcomings of the sine cosine algorithm (SCA) when applied to optimizing high-dimensional functions. This paper presents a hybrid optimization algorithm of differential evolution and sine cosine algorithm (DESCA), which combined the advantages of DE and SCA, and applied the spiral update in the WOA. Firstly, the same parameters r2 , r3 , and r4 are used to improve exploration and accelerate the convergence speed of the SCA. Secondly, the spiral update strategy of the whale optimization algorithm (WOA) is applied to update the SCA results, enhancing its exploitation. Finally, the SCA is implemented in the early stage of the DESCA, and the DE with DE/best/1 variation strategy is implemented in the late stage of the DESCA, which realizes the complementary advantages of the two algorithms and the exploration and exploitation of DESCA are well balanced. Simulation experiments on 23 benchmark functions, CEC 2014 and CEC 2020 illustrate that DESCA has higher optimization performance. In addition, two mechanical optimization problems are solved through the DESCA, which proves its practicability.