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In order to improve the performance of original artificial bee colony (ABC) algorithm for global optimization problems in terms of solution accuracy and convergence speed, a superior tracking artificial bee colony (STABC) is presented in this paper. In STABC, the updating mechanism for bees is transformed from one-dimension-wise to all-dimension-wise. In addition, this strategy enables bees always...
In this paper, a Structure-Redesigned-Based Bacterial Foraging Optimization (SRBFO) proposed in the previous work is used to reduce the computational time. Then by transplanting information communication mechanism to SRBFO, we proposed several variants of SRBFO with different topology structures, which are called SRBFO-ST, SRBFO-FC, SRBFO-Ri, SRBFO-VN and SRBFO-DN, respectively. A series of experiments...
This paper proposed an improved BFO with adaptive chemo taxis step for global optimization. A non-linearly decreasing exponential modulation model is proposed to optimize the chemo taxis step length. Four parameters: modulation index, coefficient, upper chemo taxis step length, and lower chemo taxis step length were discussed and considered to further improve the performance of BFO. To illustrate...
Bacterial foraging optimization (BFO) is a relatively new bio-heuristic algorithm which is based on a metaphor of social interaction of E. coli bacteria. Although the algorithm has successfully been applied to many kinds of real word optimization problems, experimentation with complex problems reports that the basic BFO algorithm possesses a poor performance. Thus a novel bacterial foraging optimizer...
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