Genetic algorithm designed for solving portfolio optimization problems subjected to cardinality constraint

In the present study, a new algorithm named BEXPM-RM is proposed which require no constraint handling techniques to solve portfolio optimization problems subjected to budget, cardinality, and lower/upper bound constraints. The algorithm presented combines the BEX-PM (Thakur et al. in Appl Math Compu...

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Bibliographic Details
Published in:International journal of system assurance engineering and management Vol. 9; no. 1; pp. 294 - 305
Main Authors: Jalota, Hemant, Thakur, Manoj
Format: Journal Article
Language:English
Published: New Delhi Springer India 01.02.2018
Springer Nature B.V
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ISSN:0975-6809, 0976-4348
Online Access:Get full text
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Summary:In the present study, a new algorithm named BEXPM-RM is proposed which require no constraint handling techniques to solve portfolio optimization problems subjected to budget, cardinality, and lower/upper bound constraints. The algorithm presented combines the BEX-PM (Thakur et al. in Appl Math Comput 235:292–317, 2014 ) genetic algorithm (GA) together with repair mechanism (RM) proposed by Chang et al. (Comput Oper Res 27(13):1271–1302, 2000 ). BEXPM GA tries to efficiently explore the search space whereas repair method suggested by Chang et al. ( 2000 ) ensures that a solution string is always feasible subject to the budget, cardinality, and lower/upper bound constraints. To analyze the performance of BEXPM-RM, six portfolio optimization problems are considered from the literature (Chang et al. 2000 ; Barak et al. in Eur J Oper Res 228(1):141–147, 2013 ). Among these one problem uses fuzzy set theory and others used probability theory to quantify attributes of a portfolio. In addition to these problems, a new portfolio model is formulated in fuzzy environment to analyze the effect of providing different sets of lower or/and upper bound to an asset.
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ISSN:0975-6809
0976-4348
DOI:10.1007/s13198-017-0574-z