In order to improve the global optimization of particle swarm optimization (PSO), enhance the performance of PSO in dealing with these complex, high-dimensional, multimodal optimization problems, and furthermore, promote the optimization effect in reliability optimization applications, a direct position updating-based trying-mutation PSO (DTPSO) was proposed. In this algorithm, the direct position updating strategy and trying mutation strategy are designed, which can effectively maintain the diversity of population, balance the exploitation and exploration, and increase the probability of obtaining the global optimal solution. After being verified and compared by 9 complex test functions, the rationality of algorithm design and the excellent global optimization performances were proved. In the reliability optimization, the reliability redundancy allocation and reliability allocation are optimized by different advanced improved algorithms, the comparison results prove the stability and optimization performance of DTPSO. Due to its stable and efficient global optimization performance, it is concluded the proposed DTPSO can provide effective technical support for practical applications such as reliability optimization.