On Goal-Oriented Multiobjective Embedded Optimization for System Performance Assessment

TL;DR

This paper discusses a goal-oriented multiobjective optimization approach for system performance assessment, utilizing Sequential Quadratic Programming to find solutions for complex nonlinear problems involving multiple performance indices.

Contribution

It introduces a goal-oriented multiobjective optimization framework specifically designed for system performance evaluation, applying SQP methods for nonlinear problems.

Findings

Effective formulation of system performance as a multiobjective optimization problem

Application of SQP algorithm for solving nonlinear optimization in this context

Potential for improved system assessment through goal-oriented optimization

Abstract

In this short note, we discuss a goal-oriented multiobjective optimization problem for system performance assessment. The objective function for such optimization problem, which is usually a composite of different performance indices corresponding to different operating conditions or scenarios in the system, is then posed as a goal-oriented multiobjective optimization problem. The (sub)-optimal solution(s) for such nonlinear optimization problem can be solved using a Sequential Quadratic Programming algorithm.