Model updating using genetic algorithms with sequential niche technique

Structural model updating is an optimization problem where parameters that minimize the errors between the model and the actual structure are sought. However, multiple solutions may be present. Global optimization algorithms are efficient optimisation tools but are not fully immune to missing the global minimum. To increase the chance of finding the global minimum, a combination of genetic algorithm with sequential niche technique is proposed. The method performs systematic search to find multiple minima and facilitates detecting the minimum that best describes the system. The technique is applied to experimental data from a simple laboratory structure and a full-scale pedestrian cable-stayed bridge, and also tested on a deceptive problem using the numerical model of a space frame.