Bacterial Foraging Optimization Algorithm with Dimension by Dimension Improvement
Miaomiao He, Jiajia Chen, Huiwen Deng · 2019
Bacterial Foraging Optimization (BFO) is a new nature-inspired intelligent algorithm. When solving the multidimension function optimization problem, the global update evaluation strategy will deteriorate the convergence speed and the quality of the solution due to the interference between the dimensions. Aiming at the above problems, a dimension by dimension improvement based bacterial foraging optimization algorithm is proposed. In the iterative process of our algorithm, a dimension by dimension update evaluation strategy is adopted for the solution, which combines the updated values of each dimension with those of other dimensions to form a new solution. Experimental results show that the improved strategy can effectively improve the convergence speed of BFO algorithm and improve the quality of solution. Furthermore, compared with classical BFO algorithm, the results show that the improved algorithm is competitive in solving continuous function optimization problems.