ZHAO Dan, SUN Xiangkai. Some Robust Approximate Optimality Conditions for Nonconvex Multi-Objective Optimization Problems[J]. Applied Mathematics and Mechanics, 2019, 40(6): 694-700. doi: 10.21656/1000-0887.390289
Citation: ZHAO Dan, SUN Xiangkai. Some Robust Approximate Optimality Conditions for Nonconvex Multi-Objective Optimization Problems[J]. Applied Mathematics and Mechanics, 2019, 40(6): 694-700. doi: 10.21656/1000-0887.390289

Some Robust Approximate Optimality Conditions for Nonconvex Multi-Objective Optimization Problems

doi: 10.21656/1000-0887.390289
Funds:  The National Natural Science Foundation of China(11701057)
  • Received Date: 2018-11-16
  • Rev Recd Date: 2019-04-10
  • Publish Date: 2019-06-01
  • A class of nonconvex multi-objective optimization problems were introduced with data uncertainty. Then, with the robust optimization approach, the robust counterpart model for the uncertain multi-objective optimization problem was built. Moreover, with the scalarization method and the generalized subdifferential properties, the optimality conditions were characterized for robust quasi approximate efficient solutions to the uncertain multi-objective optimization problem. The work generalizes and improves some results in the recent literatures.
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