Bacterial colony foraging optimization

Bacterial foraging optimization using novel chemotaxis and conjugation strategies

“…In [15] , authors pointed out that a fixed chemotaxis step size usually results in sustained oscillation according to mathematical analysis; they presented two simple schemes to adaptively change the chemotaxis step. More recently, Chen et al proposed two novel bacterial colony foraging algorithms: BCF [10] and BCFO [12] . Using different strategies, the two approaches extended the original BFO to an adaptive and cooperative model by combining bacterial chemotaxis, cell-to-cell communication based on a PSO pattern, and a self-adaptive foraging strategy called area concentrate search (ACS).…”

“…The first group shown in Table 1 is composed of eight classical basic functions, which are widely used in the real-parameter optimization problems [10,15,16] . The first [30] .…”

“…Moreover, we compared BFO-CC with five other better algorithms published in prestigious international journals on four functions ( f 1 , f 5 , f 6 , and f 7 ) with 30 dimensions. The five algorithms are APSO [50] , CLPSO [29] , OCABC [22] , BCF [10] , and BCFO [12] . Afterwards, to further validate performance of the BFO-CC algorithm, the seven algorithms used in the second part of the comparison experiments were tested on a more complex second group of functions with 10, 30, 50, or 100 dimensions.…”

“…Thus, a larger mutation value is conducive to avoidance of premature convergence. For this reason, most BFO algorithms set this probability value to 0.2 or 0.25 [7,10,12,15] . We also conducted a series of tuning experiments and found that the proposed BFO-CC algorithm yielded better results in most cases when the mutation probability was set to 0.25.…”

“…The other category is aimed at development of adaptive schemes for the step size to balance a local search and global search in the optimization process [11,15,33,41] . Moreover, there are some hybrid studies [10,12,52] , which simultaneously deal with both goals to more effectively improve the BFO performance.…”