This paper introduces a proposal to extend the particle swarm optimization (PSO) to deal with constrained multiobjective optimization problems. PSO is modified by using the bidirectional searching strategy to guide each particle to search simultaneously in its neighborhood and the region where particles are distributed sparsely. The advantages of the approach are that it is easy to implement and the obtained solutions has a good distribution. It is validated using several test cases. The results show that the approach can efficiently find multiple Pareto optimal solutions. Finally, the approach is used to solve buoys-arrangement problem and the results are satisfying.