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Improving the Approximated Projected Perspective Reformulation by Dual Information

Antonio, Frangioni and Fabio, Furini and Claudio, Gentile (2016) Improving the Approximated Projected Perspective Reformulation by Dual Information. Technical Report del Dipartimento di Informatica . University of Pisa, Pisa, IT. (Submitted)

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    We propose an improvement of the Approximated Projected Perspective Reformulation (AP^2R) of [Frangioni, Furini, Gentile, Computational Optimization and Applications, 2016] for the case in which constraints linking the binary variables exist. The new approach requires to solve the Perspective Reformulation (PR) once, and then use the corresponding dual information to reformulate the problem prior to applying AP^2R, thereby combining the root bound quality of the PR with the reduced relaxation computing time of AP^$R. Computational results for the cardinality-constrained Mean-Variance portfolio optimization problem show that the new approach is competitive with state-of-the-art ones.

    Item Type: Book
    Uncontrolled Keywords: Mixed-Integer NonLinear Problems, Semi-continuous Variables, Perspective Reformulation, Projection, Lagrangian Relaxation, Portfolio Optimization
    Subjects: Area01 - Scienze matematiche e informatiche > MAT/09 - Ricerca operativa
    Divisions: Dipartimenti (from 2013) > DIPARTIMENTO DI INFORMATICA
    Depositing User: Prof. Antonio Frangioni
    Date Deposited: 02 Sep 2016 13:07
    Last Modified: 16 Sep 2016 10:44
    URI: http://eprints.adm.unipi.it/id/eprint/2358

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