SCPIP
SCPIP - an efficient software tool for the solution of structural optimization problems. This paper describes SCPIP, a FORTRAN77 subroutine that has been proven to be a reliable implementation of convex programming methods in an industrial environment. Convex approximation methods like the method of moving asymptotes are used nowadays in many software packages for structural optimization. They are known to be efficient tools for the solution of design problems, in particular if displacement dependent constraints like stresses occur. A major advantage over many but not all classical approaches of mathematical programming is that at an iteration point a local model is formulated. For the solution of such a model no further function and gradient evaluations are necessary besides those at the current iteration point. The first versions of convex approximation methods used all a dual approach to solve the subproblems which is still a very efficient algorithm to solve problems with at most a medium number of constraints. But it is not efficient for problems with many constraints. An alternative is the use of an interior point method for the subproblem solution. This leads to more freedom in the definition of the linear systems where most of the computing time to solve the subproblems is spent. In consequence, large-scale problems can be handled more efficiently.
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References in zbMATH (referenced in 7 articles )
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Sorted by year (- Munro, Dirk; Groenwold, Albert A.: On sequential approximate simultaneous analysis and design in classical topology optimization (2017)
- Etman, L.F.P.; Groenwold, Albert A.; Rooda, J.E.: First-order sequential convex programming using approximate diagonal QP subproblems (2012)
- Groenwold, Albert A.: Positive definite separable quadratic programs for non-convex problems (2012)
- Schury, Fabian; Stingl, Michael; Wein, Fabian: Slope constrained material design (2012)
- Yang, Dixiong; Yang, Pixin: Numerical instabilities and convergence control for convex approximation methods (2010)
- Werme, M.: Using the sequential linear integer programming method as a post-processor for stress-constrained topology optimization problems (2008)
- Schittkowski, Klaus; Zillober, Christian: SQP versus SCP methods for nonlinear programming (2005)