Abstract
In this paper, dynamically swarm shared mutation based Bacterial Foraging (DSSBFO) is proposed to optimize multidimensional, unimodal and multimodal functions. In BFO, due to fixed step size it requires more computational cost to get optimum solution with better accuracy. Chemotaxis and reproduction step of BFO are not sufficient for an effective search. So in this paper, the authors propose dynamic step size in BFO to achieve optimum solution with better accuracy with minimum cost. The dynamic step size i.e. mutation is achieved by modifying the position equation of GLBestPSO and momentum factor (mc) of SSMPSO used in modified equation to bring the bacteria in search space and not to cross the boundary of search space. The eight standard benchmark functions are used to prove the performance of DSSBFO in terms of precision and cost. DSSBFO performs well as compared to BFO and BSO (BFO hybridized with PSO) alogrithms interms of quality solution with faster convergence.
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