An SQP Algorithm for Structural Topology Optimization Based on Majorization–Minimization Method

When applying the sequential quadratic programming (SQP) algorithm to topology optimization, using quasi-Newton methods or calculating Hessian matrix directly will result in a considerable amount of calculation, making it computationally infeasible when number optimization variables is large. To solve above problems, this paper creatively proposes method for approximate structural with minimum compliance problems. Then, second-order Taylor expansion transforms original problem into series separable and easy-to-solve convex (QP) subproblems. Finally, optimality criteria (QPOC) QP solver MATLAB are used Compared other methods, advantage proposed that diagonally positive definite its calculation simple. Numerical experiments on an MBB beam cantilever verify feasibility efficiency method.