Abstract
By using auxiliary principle technique, a new proximal point algorithm based on decomposition method is suggested for computing a weakly efficient solution of the constrained multiobjective optimization problem (MOP) without assuming the nonemptiness of its solution set. The optimality conditions for (MOP) are derived by the Lagrangian function of its subproblem and corresponding mixed variational inequality. Some basic properties and convergence results of the proposed method are established under some mild assumptions. As an application, we employ the proposed method to solve a split feasibility problem. Finally, numerical results are also presented to illustrate the feasibility of the proposed algorithm.
| Original language | English |
|---|---|
| Pages (from-to) | 289-308 |
| Number of pages | 20 |
| Journal | Computational Optimization and Applications |
| Volume | 65 |
| Issue number | 1 |
| DOIs | |
| State | Published - 1 Sep 2016 |
Bibliographical note
Publisher Copyright:© 2016, Springer Science+Business Media New York.
Keywords
- Auxiliary principle
- Decomposition method
- Mixed variational inequalities
- Multiobjective optimization with cone constraints
- Proximal point algorithm
- Split feasibility problems
ASJC Scopus subject areas
- Control and Optimization
- Computational Mathematics
- Applied Mathematics
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