Farnaz Salehi Sadaghiani - Department of Mathematical Sciences, Sharif University of Thechnology
Nezam Mahdavi-Amiri - Department of Mathematical Sciences, Sharif University of Thechnology

We propose a nonmonotone quasi-Newton algorithm for unconstrained multiobjective optimization. We give global convergence and local superlinear convergence under reasonable assumptions. Our numerical results show that the nonmonotone quasi-Newton algorithm uses fewer function evaluations than the monotone quasi-Newton algorithm

Multiobjective programming, nonmonotone quasi-Newton method, efficiency