Abstract
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.
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Niu, B., Wang, J., Wang, H., Tan, L. (2012). Bacterial-Inspired Algorithms for Engineering Optimization. In: Huang, DS., Jiang, C., Bevilacqua, V., Figueroa, J.C. (eds) Intelligent Computing Technology. ICIC 2012. Lecture Notes in Computer Science, vol 7389. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31588-6_83
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DOI: https://doi.org/10.1007/978-3-642-31588-6_83
Publisher Name: Springer, Berlin, Heidelberg
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