study seeks to solve the optimization problem of different engineering designs by using nonlinear mixed integer programming mode. In the past, this type of engineering design optimization problem has been widely studied and discussed. They are usually solved through mathematical programming method or heuristics. However, there are more constraints and more constraints that cannot be satisfied. In solving this type of problems, we used a penalty guided cooperative particle swarm optimization to avoid the disadvantage of decreased efficiency from the increase of search spatial dimension and to raise the efficiency. In resolving the problems of five engineering design problems, including system reliability design and machine parts design problem, the data from the study indicate that the solutions from cooperative particle swarm optimization are equal or better than the best-known solutions from past literature. Thus, the results of this study show that cooperative particle swarm optimization is another effective method to find solutions to optimization problems.