Sequential Approximate Optimization by Dual Method Based on Two-Point Diagonal Quadratic Approximation

이점 대각 이차 근사화 기법을 쌍대기법에 적용한 순차적 근사 최적설계

  • Received : 2010.09.15
  • Accepted : 2011.01.07
  • Published : 2011.03.01


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.


Convexity;Duality Method;Separability;Sequential Approximate Optimization;Topology Optimization;Two-Point Diagonal Quadratic Approximation


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