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Hybrid Local Search for Constrained Financial Portfolio Selection Problems

  • Conference paper
Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems (CPAIOR 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4510))

Abstract

Portfolio selection is a relevant problem arising in finance and economics. While its basic formulations can be efficiently solved through linear or quadratic programming, its more practical and realistic variants, which include various kinds of constraints and objectives, have in many cases to be tackled by approximate algorithms. In this work, we present a hybrid technique that combines a local search, as master solver, with a quadratic programming procedure, as slave solver. Experimental results show that the approach is very promising and achieves results comparable with, or superior to, the state of the art solvers.

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Authors and Affiliations

  1. DIEGM, Università degli Studi di Udine, via delle Scienze 208, I-33100, Udine, Italy

    Luca Di Gaspero & Andrea Schaerf

  2. Dipartimento di Scienze, Università “G.D’Annunzio”, viale Pindaro 42, I-65127, Pescara, Italy

    Giacomo di Tollo

  3. DEIS, Alma Mater Studiorum Università di Bologna, via Venezia 52, I-47023 Cesena, Italy

    Andrea Roli

Authors
  1. Luca Di Gaspero
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  2. Giacomo di Tollo
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  3. Andrea Roli
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  4. Andrea Schaerf
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Pascal Van Hentenryck Laurence Wolsey

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Di Gaspero, L., di Tollo, G., Roli, A., Schaerf, A. (2007). Hybrid Local Search for Constrained Financial Portfolio Selection Problems. In: Van Hentenryck, P., Wolsey, L. (eds) Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems. CPAIOR 2007. Lecture Notes in Computer Science, vol 4510. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72397-4_4

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  • DOI: https://doi.org/10.1007/978-3-540-72397-4_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72396-7

  • Online ISBN: 978-3-540-72397-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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