• Lee, Gue Myung (Department of Applied Mathematics Pukyong National University) ;
  • Son, Pham Tien (Center of Research and Development Duy Tan University, Department of Mathematics University of Dalat)
  • 투고 : 2013.04.01
  • 발행 : 2014.01.31


In this paper, we prove a necessary optimality theorem for a nonsmooth optimization problem in the face of data uncertainty, which is called a robust optimization problem. Recently, the robust optimization problems have been intensively studied by many authors. Moreover, we give examples showing that the convexity of the uncertain sets and the concavity of the constraint functions are essential in the optimality theorem. We present an example illustrating that our main assumptions in the optimality theorem can be weakened.


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  2. Some characterizations of robust optimal solutions for uncertain convex optimization problems vol.10, pp.7, 2016,
  3. Optimality and duality for robust multiobjective optimization problems vol.134, 2016,
  4. On $$\epsilon $$ϵ-solutions for robust semi-infinite optimization problems pp.1572-9281, 2018,
  5. Optimality Conditions and Duality for Robust Nonsmooth Multiobjective Optimization Problems with Constraints pp.1573-2878, 2018,
  6. Characterizations for Optimality Conditions of General Robust Optimization Problems vol.177, pp.3, 2018,
  7. On approximate solutions for nonsmooth robust multiobjective optimization problems pp.1029-4945, 2019,