In this paper, a strategy-adaptation-based bacterial foraging optimization (SABFO) algorithm is proposed to solve the optimization of complex problems. The proposed SABFO algorithm adopts the strategic approach into chmotaxis step of traditional bacterial foraging optimization (BFO). The proposed method makes each bacterium swim on different run-lengths, and increases bacterial diversity as well. Five optimization problems of nonlinear benchmark functions are used to verify the performance of SABFO. Simulation results show that the SABFO obtains better global optimal solutions than other methods.
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