Sequential approximate optimization by dual method based on two-point diagonal quadratic approximation

Seonho Park, Sangjin Jung, Seung Hyun Jeong, Dong Hoon Choi

Research output: Contribution to journalArticlepeer-review


We present a new dual sequential approximate optimization (SAO) algorithm called SD-TDQAO (sequential dual two-point diagonal quadratic approximate optimization). This algorithm solves engineering optimization problems with a nonlinear objective and nonlinear inequality constraints. The two-point diagonal quadratic approximation (TDQA) was originally non-convex and inseparable quadratic approximation in the primal design variable space. To use the dual method, SD-TDQAO uses diagonal quadratic explicit separable approximation; this can easily ensure convexity and separability. An important feature is that the second-derivative terms of the quadratic approximation are approximated by TDQA, which uses only information on the function and the derivative values at two consecutive iteration points. The algorithm will be illustrated using mathematical and topological test problems, and its performance will be compared with that of the MMA algorithm.

Original languageEnglish (US)
Pages (from-to)259-266
Number of pages8
JournalTransactions of the Korean Society of Mechanical Engineers, A
Issue number3
StatePublished - Mar 1 2011

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering


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