Abstract
In this paper, we prove that the combined homotopy interior point method for a multiobjective programming problem introduced in Ref. [1] remains valid under a weaker constrained qualification—the Mangasarian-Fromovitz constrained qualification, instead of linear independence constraint qualification. The algorithm generated by this method associated to the Karush-Kuhn-Tucker points of the multiobjective programming problem is proved to be globally convergent.
Highlights
Let n be the n -dimensional Euclidean space, and let nand denote the nonnegative and positive n, respectively
We prove that the combined homotopy interior point method for a multiobjective programming problem introduced in Ref. [1] remains valid under a weaker constrained qualification—the Mangasarian-Fromovitz constrained qualification, instead of linear independence constraint qualification
The algorithm generated by this method associated to the Karush-Kuhn-Tucker points of the multiobjective programming problem is proved to be globally convergent
Summary
Let n be the n -dimensional Euclidean space, and let nand denote the nonnegative and positive n , respectively. We prove that the combined homotopy interior point method for a multiobjective programming problem introduced in Ref. The algorithm generated by this method associated to the Karush-Kuhn-Tucker points of the multiobjective programming problem is proved to be globally convergent. Consider the following multiobjective programming problem (MOP)
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