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Hybrid local search for constrained financial portfolio selection problems. (English) Zbl 1214.91098
Van Hentenryck, Pascal (ed.) et al., Integration of AI and OR techniques in constraint programming for combinatorial optimization problems. 4th international conference, CPAIOR 2007, Brussels, Belgium, May 23–26, 2007. Proceedings. Berlin: Springer (ISBN 978-3-540-72396-7/pbk). Lecture Notes in Computer Science 4510, 44-58 (2007).
Summary: 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.
For the entire collection see [Zbl 1120.68010].
Reviewer: Reviewer (Berlin)

MSC:
91G10 Portfolio theory
68T20 Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.)
90C20 Quadratic programming
90C59 Approximation methods and heuristics in mathematical programming
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