Optimization algorithms for system integration

This work outlines the optimization algorithms involved in integrating system analysis and measured data collected from a network of sensors. The integration is required for structural health monitoring problems arising in structural dynamics and related to (1) model parameter estimation used for finite element model updating, (2) model-based damage detection in structures and (3) optimal sensor location for parameter estimation and damage detection. These problems are formulated as single- and multi-objective optimization problems of continuous or discrete-valued variables. Gradient-based, evolutionary, hybrid and heuristic algorithms are presented that effectively address issues related to the estimation of multiple local/global solutions and computational complexity arising in single and multi-objective optimization involving continuous and discrete variables.