Adaptive Bacterial Foraging Optimization Algorithm Based on Social Foraging Strategy

In 2002, K. M. Passino proposed Bacterial Foraging Optimization Algorithm (BFOA) for distributed optimization and control. Biologic foraging strategies are diverse. Based on social and intelligent foraging theory, this paper proposed an adaptive bacterial foraging optimization algorithm, and introduced six foraging operators: chaos run operator, assimilation run operator, tumble operator, swimming operator, reproduction operator and elimination-dispersal operator. Among those operators, chaos run operator, assimilation run operator and reproduction operator were redefined in accordance with social foraging strategy. And others were same with the original algorithm. Experiments were conducted on 10 multimodal unconstrained benchmark optimization problems for demonstration the effectiveness and stability. The results demonstrate remarkable performance of the proposed algorithm on all chosen benchmark functions when compared to several successful optimization techniques

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