A Frank–Wolfe based branch-and-bound algorithm for mean-risk optimization

We present an exact algorithm for mean-risk optimization subject to a budget constraint, where decision variables may be continuous or integer. The risk is measured by the covariance matrix and weighted by an arbitrary monotone function, which allows to model risk-aversion in a very individual way....

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Vydané v:	Journal of global optimization Ročník 70; číslo 3; s. 625 - 644
Hlavní autori:	Buchheim, Christoph, De Santis, Marianna, Rinaldi, Francesco, Trieu, Long
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.03.2018 Springer Springer Nature B.V
Predmet:	Algorithms Branch & bound algorithms Computer Science Continuity (mathematics) Covariance matrix Investment analysis Mathematics Mathematics and Statistics Operations Research/Decision Theory Optimization Real Functions Risk 90C10 90C90 Global optimization Mean-risk optimization 90C57 Mixed-integer programming
ISSN:	0925-5001, 1573-2916
On-line prístup:	Získať plný text
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