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.
KeywordsEngineering problem constrained handling optimization bacterial foraging linear decreasing chemotaxis non-linear decreasing chemotaxis
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