Masaru Ito

A proximal gradient method with adaptive backtracking for weakly smooth multiobjective optimization

The proposed proximal gradient method with adaptive linesearch for multiobjective optimization problems whose objective functions are weakly smooth, i.e., they have Holder continuous gradients and the algorithm accepts coercer stationarity measure compared to existing methods is established.