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Refail Kasimbeyli, K. Gulnaz Bulbul, Behnam Soleimani, Gurkan Ozturk, Computing the set of optimal points for nonconvex multi-objective optimization problems

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DOI: 10.23952/jnva.10.2026.4.08

Volume 10, Issue 4, 1 August 2026, Pages 845-866

 

Abstract. This paper proposes a new method for computing a set of optimal points, namely, minimal, properly minimal, and weakly minimal points, and approximate optimal points for nonconvex multi-objective problems, based on a given set of weights and reference points. This is an iterative method that utilizes the scalarizing functions of both the Conic Scalarization and the Pascoletti-Serafini methods at each iteration. The convergence of the proposed method is proven, and it is demonstrated that the method terminates in a finite number of iterations for a specified error accuracy. The performance of the method is illustrated through numerical examples.

 

How to Cite this Article:
R. Kasimbeyli, K. Gulnaz Bulbul, B. Soleimani, G. Ozturk, Computing the set of optimal points for nonconvex multi-objective optimization problems, J. Nonlinear Var. Anal. 10 (2026), 845-866.