Bacterial-Inspired Algorithms for Engineering Optimization

Bio-inspired optimization techniques using analogy of swarming principles and social behavior in nature have been adopted to solve a variety of problems. In this paper, Bacterial foraging optimization (BFO) was employed to achieve high-quality solutions to engineering optimization problems. Two modifications of BFO, BFO with linear decreasing chemotaxis step (BFO-LDC) and BFO with non-linear decreasing chemotaxis step (BFO-NDC) were proposed to further improve the performance of the original algorithm. In order to illustrate the efficiency of the proposed method (BFO-LDC and BFO-NDC) for engineering problem, an engineering design problem was selected as testing functions, and the performance is compared against some state-of-the-art approaches. The experimental results demonstrated that the modified BFOs are of greater efficiency and can be used as general approach for engineering problems.