Journal of Applied and Numerical Optimization

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DOI: 10.23952/jano.8.2026.2.05
Volume 8, Issue 2, 1 August 2026, Pages 233-251

 

Abstract. We develop a general algorithm for solving constrained multiobjective optimization problems. Our approach builds on the sequential upper approximation method already used in the framework of scalar optimization, in which a nonlinear optimization problem is solved by solving a sequence of simpler problems where the objective and constraint functions upper estimate those of the original problem. For a broad class of problems, we show that every cluster point of the sequence generated by our algorithm satisfies KKT-type conditions expressed in terms of directional derivatives. Finally we end with some numerical tests to illustrate the behavior of our algorithm.

 

How to Cite this Article:
A. Fadil, A. Ghazi, A. Roubi, Sequential upper approximation method for solving multiobjective optimization problems, J. Appl. Numer. Optim. 8 (2026), 233-251.