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In this paper we investigate a class of cardinality-constrained portfolio selection problems. We construct convex relaxations for this class of optimization problems via a new Lagrangian decomposition scheme. We show that the dual problem can be reduced to a second-order cone program problem...
Persistent link: https://www.econbiz.de/10010896430
The rank function rank(.) is neither continuous nor convex which brings much difficulty to the solution of rank minimization problems. In this paper, we provide a unified framework to construct the approximation functions of rank(.), and study their favorable properties. Particularly, with two...
Persistent link: https://www.econbiz.de/10010994108
Persistent link: https://www.econbiz.de/10010994176
based on regular (in general nonconvex) nonlinear programs (NLP) solved by a (black-box) deterministic global NLP solver …
Persistent link: https://www.econbiz.de/10011151238
This paper presents the surrogate model based algorithm SO-I for solving purely integer optimization problems that have computationally expensive black-box objective functions and that may have computationally expensive constraints. The algorithm was developed for solving global optimization...
Persistent link: https://www.econbiz.de/10010994191
Persistent link: https://www.econbiz.de/10008456018