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Article summary:

1. E-superefficiency of vector optimization problems: The article introduces the concept of E-superefficiency, which is an extension of the classical concept of superefficiency in vector optimization problems. This concept is based on improved sets and aims to find optimal solutions.

2. Necessary and sufficient conditions for optimality: The article establishes a vector optimization problem using adjacent E-subconvexity in real locally convex topological linear spaces. It provides necessary and sufficient conditions for the optimality of E-super-efficient solutions. These conditions help determine the most optimal solution to the problem.

3. Generalization to approximate solutions: The article also generalizes some existing results to approximate solutions. This means that even if an exact optimal solution cannot be found, there are methods to find approximate solutions that still meet certain criteria. This expands the applicability of the E-superefficiency concept in practical scenarios.

Overall, the article focuses on introducing and analyzing the concept of E-superefficiency in vector optimization problems, providing conditions for optimality, and extending these concepts to approximate solutions.

Article analysis:


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