Sequential Convex Programming for Free Material Optimization with Displacement and Stress Constraints

S. Ertel, K. Schittkowski, C. Zillober, PLATO朜 Public Report PU朢𣇼008, Department of Computer Science, University of Bayreuth (2008)
Abstract: We consider a numerical method for constrained nonlinear programming, that is widely used in mechanical engineering and that is known under the name SCP for sequential convex programming. The algorithm consists of solving a sequence of convex and separable subproblems, where an augmented Lagrangian merit function is used for guaranteeing convergence. Originally, SCP methods were developed in structural mechanical optimization, and are particularly applied to solve topology optimization problems. A new challenge for SCP methods is the solution of free material optimization (FMO) problems which contain additional semidefinite variables and even nonlinear semi-definite matrix constraints. A few formulations are investigated in more details and possible solution approaches are outlined.

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