This paper designs a new kind of structured population and evolutionary operators to form a novel algorithm, Organizational Evolutionary Algorithm (OEA), for solving constrained optimization problems. A simple and non problem-dependent technique is incorporated into OEA to handle the constraints. In OEA, a population consists of organizations, and an organization consists of individuals. All evolutionary operators are designed to simulate the interaction among organizations. In experiments, 4 well-studied engineering design problems are used to test the performance of OEA. The results show that OEA obtains good results both in the solution quality and the computational cost.