@inbook {IOPORT.06105326,
    author       = {Niu, Ben and Wang, Jingwen and Wang, Hong and Tan, Lijing},
    title        = {Bacterial-inspired algorithms for engineering optimization.},
    year         = {2012},
    booktitle    = {Intelligent computing technology. 8th international conference, ICIC 2012, Huangshan, China, July 25--29, 2012. Proceedings},
    isbn         = {978-3-642-31587-9},
    pages        = {649-656},
    publisher    = {Berlin: Springer},
    doi          = {10.1007/978-3-642-31588-6_83},
    abstract     = {Summary: 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.},
    identifier   = {06105326},
}