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Many real world engineering optimization problems are nonlinear and constrained, meaning that objective functions are to be optimized under given constraints. Solving these problems has been challenging for many decades even until now. This paper proposes a constrained particle swarm optimization (PSO) algorithm with the stagnation detection and dispersion mechanism that can detect a probable stagnation and is able to disperse particles. This algorithm will be described and its performance is evaluated using three well-known constrained engineering problems that are widely used in literature. The results show a promising alternative path for solving the common problem of local optima in PSO algorithms for handling constrained optimization problems.