Uniformly sampled genetic algorithm with gradient search for structural identification – Part II: Local search

This paper investigates several gradient local search methods as an enhancement to Part I, to further improve the computational efficiency while achieving the same identification accuracy. The present study is significant in several ways. First, this study reveals the characteristics of structural identification from the optimization perspective. Second, the “switch point” from global search to local search is determined with due consideration in convergence speed and avoidance of local optima. Finally, the combined strategy based on Part I and Part II with a particular local search (BFGS) is found to achieve substantial improvement in identification efficiency and accuracy.