Regularization for Parameter Identification Using Multi-Objective Optimization

Summary. Regularization is a technique used in finding a stable solution when a parameter identification problem is exposed to considerable errors. However a significant difficulty associated with it is that the solution depends upon the choice of the value assigned onto the weighting regularization parameter participating in the corresponding formulation. This chapter initially and briefly describes the weighted regularization method. It continues by introducing a weightless regularization approach that reduces the parameter identification problem to multi-objective optimization. Subsequently, a gradient-based multi-objective optimization method with Lagrange multipliers, is presented. Comparative numerical results with explicitly defined objective functions demonstrate that the technique can search for appropriate solutions more efficiently than other existing techniques. Finally, the technique was successfully applied for the parameter identification of a material model 1 .

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