## 1 Introduction  
Structural identification of constructed systems typically requires the integration of structural conceptualization, finite element (FE) modeling, experimental execution, data processing, model calibration, simulation, interpretation and decisions [1]. Experimental responses are related to the physical properties of the system, and changes in these physical quantities are reflected as a change in the experimental responses. Therefore, in order to identify the actual physical characteristics of structures, it is necessary to carry out field tests and measure the resulting responses to correlate and validate the associated FE models. Both static and dynamic tests can be carried out on the actual structure for structure assessment. FE models are mathematical models that provide a means of predicting characteristic responses of structures without actually building them. In FE models, the continuous domain of the actual physical structure with infinite degrees of freedom (DOF) is discretized into small components called FEs. These models have been extensively used in industrial and research applications as they give a reasonable representation of the actual structure, but they are prone to certain inaccuracies and errors [2]. Structure health monitoring (SHM) is defined as tracking the structural responses, possibly along with inputs, over a sufficiently long duration to determine deterioration, anomalies and damage in a structure, in order to make optimal decisions for asset management [3]. More specifically, the responses of the system should be measured in such a way that any operational incidents, damage or anomalies that can affect the serviceability and reliability of the structure are detected [4]. Model updating is a branch of optimization wherein the differences in the experimental responses and their FE model counterparts are minimized using mathematical techniques. Generally, in model updating and damage assessment problems, not only is a good correlation required between experimental and analytical results, but also the updated parameters should have physical significance. The success of model updating is dependent on three key factors, setting up of the objective function, the selection of parameters and a robust optimization algorithm [5]. A proper objective function is necessary to effectively minimize the difference between the experimental and analytical results. Selection of parameters is an important issue as there may be many sets of parameters that can produce acceptable results. A robust optimization algorithm is required to find the minimum in the search space. The algorithm should be able to find a global minimum out of many local minima with precision and accuracy. The key step is to define residual vectors for the experimental and analytical values in terms of experimental frequencies and mode shapes. The residual vectors lead to objective functions that can contain different criteria for finding out the discrepancies between the experiment and FE model such as differences of frequencies, model coordinates, modal assurance criteria (MAC), coordinate modal assurance criteria (COMAC) and others [6]. It is the goal of optimization to minimize the error residual to determine a set of physically-justifiable parameters [7]. The outcome of a model updating application to a constructed system should be an analytical model that can replicate the actual mechanical characteristics of the built structure with a good level of confidence. Damage detection of civil structures is a difficult optimization problem. The algorithm capability and search domain complexity are the two main aspects to be considered [8]. The sensitivity method (SM) is traditionally used for model updating and damage assessment, but it is prone to be attracted to local minima, which may lead to a solution with no physical significance. In certain cases, manual model updating has to be done in SM, and even then, the global solution is not confirmed [9]. Different objective functions have also been tried using SM.