First-order sequential convex programming using approximate diagonal QP subproblems
| dc.contributor.author | Etman L.F.P. | |
| dc.contributor.author | Groenwold A.A. | |
| dc.contributor.author | Rooda J.E. | |
| dc.date.accessioned | 2012-06-06T08:02:30Z | |
| dc.date.available | 2012-06-06T08:02:30Z | |
| dc.date.issued | 2012 | |
| dc.description.abstract | Optimization algorithms based on convex separable approximations for optimal structural design often use reciprocal-like approximations in a dual setting; CONLIN and the method of moving asymptotes (MMA) are well-known examples of such sequential convex programming (SCP) algorithms. We have previously demonstrated that replacement of these nonlinear (reciprocal) approximations by their own second order Taylor series expansion provides a powerful new algorithmic option within the SCP class of algorithms. This note shows that the quadratic treatment of the original nonlinear approximations also enables the restatement of the SCP as a series of Lagrange-Newton QP subproblems. This results in a diagonal trust-region SQP type of algorithm, in which the second order diagonal terms are estimated from the nonlinear (reciprocal) intervening variables, rather than from historic information using an exact or a quasi-Newton Hessian approach. The QP formulation seems particularly attractive for problems with far more constraints than variables (when pure dual methods are at a disadvantage), or when both the number of design variables and the number of (active) constraints is very large. © The Author(s) 2011. | |
| dc.identifier.citation | Structural and Multidisciplinary Optimization | |
| dc.identifier.citation | 45 | |
| dc.identifier.citation | 4 | |
| dc.identifier.citation | 479 | |
| dc.identifier.citation | 488 | |
| dc.identifier.issn | 1615147X | |
| dc.identifier.other | doi:10.1007/s00158-011-0739-3 | |
| dc.identifier.uri | http://hdl.handle.net/10019.1/21345 | |
| dc.subject | Diagonal quadratic approximation | |
| dc.subject | Reciprocal intervening variables | |
| dc.subject | Sequential approximate optimization (SAO) | |
| dc.subject | Sequential convex programming (SCP) | |
| dc.subject | Sequential quadratic programming (SQP) | |
| dc.subject | Trust region method | |
| dc.title | First-order sequential convex programming using approximate diagonal QP subproblems | |
| dc.type | Article |