Abstract:

In order to improve the performance of the BFA(Bacterial Foraging Algorithm), Bacterial foragingalgorithm and immune algorithm were combined, the clonal selection ideas in immune algorithm were used toreplace the reproduction operation of BFA. For the chemotaxis operation, the moving step of bacteria is shortenby the iteration proceeding, so that the astringency is guaranteed, and the overall searching capability of bacteriais ensured. The elimination and dispersal operation is improved by guaranteeing the bacterial with the highestfitting value not be dispelled to increase the astirngency accuracy. The results show that the optimal value whichwas obtained by the authors were closer to the optimal value than BFA's, which proved the algorithm was morecapable in optimization. Moreover, the algorithm was more stable because the variance of three functions were all less than BFA's.

Key words: bacterial foraging algorithm, immune algorithm, optimized