Abstract
To address the problems of weak quorum sensing ability and slow convergence speed in bacterial foraging algorithm, a bacterial foraging algorithm with potential field guidance mechanism is proposed. The algorithm combines the sampling guidance mechanism in the artificial potential field algorithm to provide the optimization direction for each bacterium; The original swimming operation of bacterial foraging algorithm is used to realize the local optimization strategy, and the local dimension update is added after swimming, so that the search range of bacteria in chemotaxis operation is wider; In the elimination and dispersal operation of bacterial foraging algorithm, double Gaussian function is introduced to re initialize the location of bacteria, so as to better avoid the algorithm falling into local extremum and improve the optimization ability of the algorithm. The experimental results show that the improved bacterial foraging algorithm has better optimization ability than the basic bacterial foraging algorithm.
Bacterial Foraging Based Algorithm Front-end to Solve Global Optimization Problems
