A First-Order Multi-Gradient Algorithm for Multi-Objective Bi-Level Optimization

Understand

In this paper, we study the Multi-Objective Bi-Level Optimization (MOBLO) problem, where the upper-level subproblem is a multi-objective optimization problem and the lower-level subproblem is for scalar optimization.

• Existing gradient-based MOBLO algorithms need to compute the Hessian matrix, causing the computational inefficient problem.
• To address this, we propose an efficient first-order multi-gradient method for MOBLO, called FORUM.
• Specifically, we reformulate MOBLO problems as a constrained multi-objective optimization (MOO) problem via the value-function approach.