ARTIFICIAL BEE COLONY (ABC) METHOD FOR PORTOFOLIO OPTIMIZATION
Nature-inspired optimization methods have been known to have the capability of handling computationally complicated problems, especially when traditional methods have become insufficient to. Artificial Bee Colony (ABC) is a method inspired by foraging bahaviour of honey bee. In this thesis, writer...
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| Format: | Theses |
| Language: | Indonesia |
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| Online Access: | https://digilib.itb.ac.id/gdl/view/33720 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | Nature-inspired optimization methods have been known to have the capability of handling computationally complicated problems, especially when traditional methods have become insufficient to. Artificial Bee Colony (ABC) is a method inspired by foraging bahaviour of honey bee.
In this thesis, writer used modified Artificial Bee Colony (mABC) method to solve Markowitz portofolio optimization problems. The optimization problem focused on optimization without constraint, with buy-in threshold constraint, roundlot constraint, and cardinality constraint. First, writer used mABC to solve benchmark function optimization, including continuous function and Mix-Integer Linear-Non Linear Function (MINLP), then solve the Markowitz portofolio optimization problems. Writer modified the ABC method to handle integer and mix-integer non linear programming problems. The result confirm that mABC method is capable to solve Markowitz portofolio optimization problems. |
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