Artificial bee colony algorithm for constrained possibilistic portfolio optimization problem

Wei Chen

Physica A: Statistical Mechanics and its Applications, 2015, vol. 429, issue C, 125-139

Abstract: In this paper, we discuss the portfolio optimization problem with real-world constraints under the assumption that the returns of risky assets are fuzzy numbers. A new possibilistic mean-semiabsolute deviation model is proposed, in which transaction costs, cardinality and quantity constraints are considered. Due to such constraints the proposed model becomes a mixed integer nonlinear programming problem and traditional optimization methods fail to find the optimal solution efficiently. Thus, a modified artificial bee colony (MABC) algorithm is developed to solve the corresponding optimization problem. Finally, a numerical example is given to illustrate the effectiveness of the proposed model and the corresponding algorithm.

Keywords: Fuzzy portfolio optimization; Semiabsolute deviation; Cardinality constraint; Artificial bee colony algorithm; Heuristics (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:429:y:2015:i:c:p:125-139

DOI: 10.1016/j.physa.2015.02.060

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