Abstract
We analyze a class of sublinear functionals which characterize the interior and the exterior of a convex cone in a normed linear space.
References
- L. M. Graña Drummond, A. N. Iusem: A projected gradient method for vector optimization problems, Comput. Optim. Appl. 28(1) (2004) 5–29.https://doi.org/10.1023/B:COAP.0000018877.86161.8bGoogle Scholar
- J. Fliege, L. M. Graña Drummond, B. F. Svaiter: Newton’s method for multiobjective optimization, SIAM J. Optim. 20(2) (2009) 602–626.https://doi.org/10.1137/08071692XGoogle Scholar
- J. Fliege, B. F. Svaiter: Steepest descent methods for multicriteria optimization, Math. Methods Oper. Res. 51(3) (2000) 479–494.https://doi.org/10.1007/s001860000043Google Scholar
- L. M. Graña Drummond, B. F. Svaiter: A steepest descent method for vector optimization. J. Comput. Appl. Math. 175(2) (2005) 395–414.https://doi.org/10.1016/j.cam.2004.06.018Google Scholar
- J.-B. Hiriart-Urruty: Tangent cones, generalized gradients and mathematical programming in Banach spaces, Math. Oper. Res. 4(1) (1979) 79–97.https://doi.org/10.1287/moor.4.1.79Google Scholar
- M. C. Travain: On Lagrange-Kuhn-Tucker multipliers for Pareto optimization problems, Numer. Funct. Anal. Optim. 15(5–6) (1994) 689–693.https://doi.org/10.1080/01630569408816587Google Scholar
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Published by Heldermann Verlag, 2014. Rights now held by Banach Press LLC.
