A micro-bacterial foraging algorithm for high-dimensional optimization

Very recently bacterial foraging has emerged as a powerful technique for solving optimization problems. In this paper, we introduce a micro-bacterial foraging optimization algorithm, which evolves with a very small population compared to its classical version. In this modified bacterial foraging algorithm, the best bacterium is kept unaltered, whereas the other population members are reinitialized. This new small population mu-BFOA is tested over a number of numerical benchmark problems for high dimensions and we find this to outperform the normal bacterial foraging with a larger population as well as with a smaller population.