Investigates convergence in vector optimization with two criteria, suggesting enhanced methods.
The paper provides new results on the convergence of the linear convolution method to solutions of vector optimization problems with two criteria in the absence of convexity properties. Utilization of the regularization method for enhancing convergence is also substantiated. It is proposed to take a scalar minimum point with respect to one criterion subject to the constraint for the second criterion represented by its control estimate as a solution to the initial vector problem.
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I. V. Konnov (2026) studied this question.
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