In order to solve the problem of low calculation accuracy and slow convergence velocity of the Yin-Yang pair optimization (YYPO) algorithm, a novel YYPO (NYYPO) algorithm based on the wavelet elite solutions learning and multi-angle search is presented in this paper. Firstly, the strategy of wavelet elite solutions learning is proposed to make full use of the evolutionary information of elite solutions. High-quality solutions generated by this strategy are used in the global exploration and local exploitation of the algorithm. Then, the search angle is introduced into the solution update equation, which can realize the all-round search for the algorithm search space. The convergence of the proposed algorithm is analyzed. The continuous functions and the bottleneck traveling salesman problem are employed in the numerical experiments. The NYYPO is compared with many intelligent optimization algorithms. Experimental results demonstrate that the presented NYYPO algorithm has better optimization performance.