Reliability and optimization are two key elements for structural design. The reliability-based topology optimization (RBTO) is a powerful and promising methodology for finding the optimum topologies with the uncertainties. In this paper, the particle swarm algorithm (PSO) using performance measure approach (PMA) is proposed in the RBTO procedure. Conventionally, the approximate limit state function along with the most probable point (MPP) search algorithms is used for calculation the reliability index. On the other hand, the choice of penalty function for having a convergent search plays a critical role. In addition one does not need to use approximate limit state function and calculating the derivatives of limit state function with respect to random variables. Furthermore, the convergence problem of the MPP search algorithms for complicated limit state functions does not exist. This paper presents RBTO using bi-directional evolutionary structural optimization (BESO) with an improved filter scheme. The topologies obtained by RBTO are compared with that of obtained by deterministic topology optimization (DTO). Results of the RBTO using PSO show that PSO can be effectively applied to RBTO and its use is quite simple.