Lijing Tan
Management School, Jinan University, Guangzhou, China
Ben Niu
College of Management, Shenzhen University, Shenzhen, China
Fuyong Lin
Management School, Jinan University, Guangzhou, China
Qiqi Duan
College of Management, Shenzhen University, Shenzhen, China
Li Li
College of Management, Shenzhen University, Shenzhen, China
ABSTRACT
Bacterial Foraging Optimizer (BFO) is a very recent swarm intelligence technique inspired by the foraging behavior of Escherichia coli (E. coli). The key step in BFO is the chemotaxis movement of bacteria, which models a trial of solutions of the optimization problems. Based on our previous work, we proposed a modified BFO (MBFO), where a linear decreasing chemotaxis step mechanism is incorporated into run and swim step of chemotatix cycle of original BFO. To illustrate the efficiency of the proposed algorithm, a constrained Markowitz model with transaction fee and short sales were taken as a test example. On the basis of the numerical results, we can conclude that the proposed method can provide the more flexible and accurate results than those obtained by original BFO and PSO.
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How to cite this article
Lijing Tan, Ben Niu, Fuyong Lin, Qiqi Duan and Li Li, 2013. Modified Bacterial Foraging Optimization for Constrained Portfolio Optimization. Information Technology Journal, 12: 7918-7921.
DOI: 10.3923/itj.2013.7918.7921
URL: https://scialert.net/abstract/?doi=itj.2013.7918.7921
DOI: 10.3923/itj.2013.7918.7921
URL: https://scialert.net/abstract/?doi=itj.2013.7918.7921
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