Generalized Optimality Criteria Method for Topology Optimization

In this article, a generalized optimality criteria method is proposed for topology optimization with arbitrary objective function and multiple inequality constraints. This algorithm uses sensitivity information to update both the Lagrange multipliers design variables. Different from conventional method, does not satisfy constraints at every iteration. Rather, it improves variables such that are satisfied upon convergence. The main advantages of its capability handling computational efficiency. numerical examples, was found be more than 100 times faster 1000 moving asymptotes.