To solve the premature convergence problem of the basic Yin-Yang-Pair Optimization (YYPO) algorithm, the chaos search was introduced to the algorithm to explore more areas based on the ergodicity of chaos, so as to improve the global exploration capability. Besides, based on the intricate operator of I Ching, opposition-based learning was adopted to search for the opposite solutions to the current ones in order to improve the local exploitation ability. The design of parallel programming was also added to the algorithm to make full use of computing resources such as multi-core processors. Benchmark functions were used for numerical experiments to test the performance of the improved YYPO algorithm combined with chaos search and intricate operator, namely CSIOYYPO. Experimental results show that, compared with YYPO algorithms including basic YYPO algorithm and adaptive YYPO algorithm as well as other intelligent optimization algorithms, CSIOYYPO algorithm has higher calculation accuracy and higher convergence speed.