Strong duality with super efficiency in set-valued optimization

This paper is devoted to the study of four dual problems of a primal vector optimization problem involving nearly subconvexlike set-valued mappings. For each dual problem, a strong duality theorem with super efficiency is established. The strong duality result can be expressed as follows: starting from a super minimizer of the primal problem, a super maximizer of the dual problem can be constructed such that the corresponding objective values of both problems are equal. The results improve the corresponding ones in the literature. (C) 2017 All rights reserved.