An Algorithm for Vector Optimization Problems
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Abstract
In this paper, we consider of finding efficient solution and weakly efficient solution for nonconvex vector optimization problems. When X and Y are normed spaces, F is an anti-Lipschitz mapping from X to Y, and the ordering cone is regular, we present an algorithm to guarantee that the generated sequence converges to an efficient solution with respect to normed topology. If the domain of the mapping is compact, we prove that the generated sequence converges to an efficient solution with respect to normed topology without requiring that mapping is anti-Lipschitz. We also give an algorithm to guarantee that the generated sequence converges to a weakly efficient solution with respect to normed topology.
Keywords
Vector optimization problems Efficient solution Weakly efficient solution AlgorithmMathematics Subject Classification
90C26 90C29References
- 1.Fliege, J., Svaiter, B.F.: Steepest descent methods for multicriteria optimization. Math. Methods Oper. Res. 51, 479–494 (2000)MathSciNetCrossRefMATHGoogle Scholar
- 2.Drummond, L.M.G., Iusem, A.N.: A projected gradient method for vector optimization problems. Comput. Optim. Appl. 28, 5–30 (2004)MathSciNetCrossRefMATHGoogle Scholar
- 3.Bonnel, H., Iusem, A.N., Svaiter, B.F.: Proximal methods in vector optimization. SIAM J. Optim. 15, 953–970 (2005)MathSciNetCrossRefMATHGoogle Scholar
- 4.Rockafellar, R.T.: Monotone operators and the proximal point algorithm. SIAM J. Control Optim. 14, 877–898 (1976)MathSciNetCrossRefMATHGoogle Scholar
- 5.Ceng, L.C., Yao, J.C.: Approximate proximal methods in vector optimization. Euro. J. Oper. Res. 183(1), 1–19 (2007)MathSciNetCrossRefMATHGoogle Scholar
- 6.Chen, Z., Zhao, K.: A proximal-type method for convex vector optimization problem in Banach spaces. Numer. Funct. Anal. Optim. 30, 1–12 (2009)MathSciNetCrossRefGoogle Scholar
- 7.Chen, Z., Xiang, C.H., Zhao, K.Q., Liu, X.W.: Convergence analysis of Tikhonov-type regularization algorithms for multiobjective optimization problems. Appl. Math. Comput. 211, 167–172 (2009)MathSciNetMATHGoogle Scholar
- 8.Jayswal, A., Choudhury, S.: An exact \(l_1\) exponential penalty function method for multiobjective optimization problems with exponential-type invexity. J. Oper. Res. Soc. Chin. 2, 75–91 (2014)MathSciNetCrossRefMATHGoogle Scholar
- 9.Jahn, J.: Mathematical Vector Optimization in Partially-Ordered Linear Spaces. Peter Lang, Frankfurt an Main (1986)MATHGoogle Scholar
- 10.Deimling, K.: Nonlinear Functional Analysis. Springer-Verlag, Berlin (1988)MATHGoogle Scholar
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