Nature Inspired Intelligence for the Constrained Portfolio Optimization Problem

Authors:
Vassilios Vassiliadis;Georgios Dounias
Affiliations:
Management and Decision Engineering Laboratory, Department of Financial & Management Engineering, School of Business Studies, University of the Aegean, Greece GR-821 00;Management and Decision Engineering Laboratory, Department of Financial & Management Engineering, School of Business Studies, University of the Aegean, Greece GR-821 00
Venue:
SETN '08 Proceedings of the 5th Hellenic conference on Artificial Intelligence: Theories, Models and Applications
Year:
2008

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Abstract

In this paper, we apply a basic Bee Colony Optimization algorithm in order to find a high-quality solution for the constrained portfolio optimization problem. Moreover, we use a basic Ant Colony Optimization algorithm and a Tabu Search metaheuristic approach as a benchmark. Our findings indicate that nature-inspired methodologies are able to find feasible solutions for dynamic optimization problems in a reasonable amount of time in contrast with the simple tabu search.