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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| Published in: | International journal of system assurance engineering and management Vol. 9; no. 1; pp. 294 - 305 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
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New Delhi
Springer India
01.02.2018
Springer Nature B.V |
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| ISSN: | 0975-6809, 0976-4348 |
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| Abstract | 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. |
|---|---|
| AbstractList | 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. 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. |
| Author | Jalota, Hemant Thakur, Manoj |
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| Cites_doi | 10.1016/S0305-0548(99)00074-X 10.1016/j.ejor.2012.08.023 10.1007/978-3-540-73165-8_5 10.1088/1469-7688/1/5/301 10.1016/S0377-2217(01)00175-8 10.1016/S0045-7825(99)00389-8 10.1007/BF02282055 10.1016/j.eswa.2011.09.129 10.1016/S0165-0114(99)80004-9 10.1016/j.ejor.2013.01.036 10.1007/978-3-540-77926-1 10.1016/S0019-9958(65)90241-X 10.1016/j.ins.2012.12.011 10.1109/TEVC.2012.2196800 10.1016/j.camwa.2007.06.019 10.1007/978-3-7908-1817-8_7 10.1109/TFUZZ.2012.2227487 10.2307/1907413 10.1016/j.amc.2009.02.044 10.1016/j.amc.2005.11.027 10.4018/978-1-4666-9888-8.ch004 10.1016/j.amc.2007.03.046 10.1016/j.amc.2014.02.093 |
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| Keywords | Swap mutation Real-coded genetic algorithms Budget Bounded exponential crossover Cardinality and lower/upper bound constraints |
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| SubjectTerms | Engineering Engineering Economics Fuzzy logic Fuzzy set theory Fuzzy sets Genetic algorithms Logistics Marketing Optimization Organization Original Article Probability theory Quality Control Reliability Repair Safety and Risk Upper bounds |
| Title | Genetic algorithm designed for solving portfolio optimization problems subjected to cardinality constraint |
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