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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Vydané v:International journal of system assurance engineering and management Ročník 9; číslo 1; s. 294 - 305
Hlavní autori: Jalota, Hemant, Thakur, Manoj
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New Delhi Springer India 01.02.2018
Springer Nature B.V
Predmet:
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
Swap mutation
Real-coded genetic algorithms
Budget
Bounded exponential crossover
Cardinality and lower/upper bound constraints
ISSN:0975-6809, 0976-4348
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Shrnutí: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.
Bibliografia:ObjectType-Article-1
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ISSN:0975-6809
0976-4348
DOI:10.1007/s13198-017-0574-z