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The paper presents a modified particle swarm optimization (PSO) algorithm for engineering optimization problems with constraints. PSO is started with a group of feasible solutions and a feasibility function is used to check if the newly explored solutions satisfy all the constraints. All the particles keep only those feasible solutions in their memory. Several engineering design optimization problems were tested and the results show that PSO is an efficient and general approach to solve most nonlinear optimization problems with inequity constraints.