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Epsilon-dominating solutions in mean-variance portfolio analysis

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  • White, D.J.

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  • White, D.J., 1998. "Epsilon-dominating solutions in mean-variance portfolio analysis," European Journal of Operational Research, Elsevier, vol. 105(3), pages 457-466, March.
    • Handle: RePEc:eee:ejores:v:105:y:1998:i:3:p:457-466
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    References listed on IDEAS

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    1. Bruce Faaland, 1974. "An Integer Programming Algorithm for Portfolio Selection," Management Science, INFORMS, vol. 20(10), pages 1376-1384, June.
    2. Jong-Shi Pang, 1980. "A New and Efficient Algorithm for a Class of Portfolio Selection Problems," Operations Research, INFORMS, vol. 28(3-part-ii), pages 754-767, June.
    3. B. Blog & G. van der Hoek & A. H. G. Rinnooy Kan & G. T. Timmer, 1983. "The Optimal Selection of Small Portfolios," Management Science, INFORMS, vol. 29(7), pages 792-798, July.
    4. Andre F. Perold, 1984. "Large-Scale Portfolio Optimization," Management Science, INFORMS, vol. 30(10), pages 1143-1160, October.
    5. D. J. White, 1995. "Finite Horizon Markov Decision Processes with Uncertain Terminal Payoffs," Operations Research, INFORMS, vol. 43(5), pages 862-869, October.
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    Cited by:

    1. Engau, Alexander & Wiecek, Margaret M., 2007. "Generating [epsilon]-efficient solutions in multiobjective programming," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1566-1579, March.
    2. Ellen H. Fukuda & L. M. Graña Drummond & Fernanda M. P. Raupp, 2016. "An external penalty-type method for multicriteria," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 24(2), pages 493-513, July.
    3. Bodnar, Taras & Parolya, Nestor & Schmid, Wolfgang, 2013. "On the equivalence of quadratic optimization problems commonly used in portfolio theory," European Journal of Operational Research, Elsevier, vol. 229(3), pages 637-644.
    4. N. Mahdavi-Amiri & F. Salehi Sadaghiani, 2017. "Strictly feasible solutions and strict complementarity in multiple objective linear optimization," 4OR, Springer, vol. 15(3), pages 303-326, September.
    5. C. Gutiérrez & B. Jiménez & V. Novo, 2006. "On Approximate Efficiency in Multiobjective Programming," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 64(1), pages 165-185, August.
    6. Xiaopeng Zhao & Jen-Chih Yao, 2022. "Linear convergence of a nonmonotone projected gradient method for multiobjective optimization," Journal of Global Optimization, Springer, vol. 82(3), pages 577-594, March.
    7. O. Schütze & C. Hernández & E-G. Talbi & J. Q. Sun & Y. Naranjani & F.-R. Xiong, 2019. "Archivers for the representation of the set of approximate solutions for MOPs," Journal of Heuristics, Springer, vol. 25(1), pages 71-105, February.
    8. Ellen Fukuda & L. Graña Drummond, 2013. "Inexact projected gradient method for vector optimization," Computational Optimization and Applications, Springer, vol. 54(3), pages 473-493, April.
    9. G. Cocchi & M. Lapucci, 2020. "An augmented Lagrangian algorithm for multi-objective optimization," Computational Optimization and Applications, Springer, vol. 77(1), pages 29-56, September.
    10. Matteo Lapucci & Pierluigi Mansueto, 2023. "A limited memory Quasi-Newton approach for multi-objective optimization," Computational Optimization and Applications, Springer, vol. 85(1), pages 33-73, May.
    11. Xiaopeng Zhao & Markus A. Köbis & Yonghong Yao & Jen-Chih Yao, 2021. "A Projected Subgradient Method for Nondifferentiable Quasiconvex Multiobjective Optimization Problems," Journal of Optimization Theory and Applications, Springer, vol. 190(1), pages 82-107, July.

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