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During the course of evolution living organisms have developed a very complex behavior, sophisticated communication capabilities, distributed colony control, group foraging strategies, and a high degree of cooperation when tackling tasks. Bio-inspired optimization techniques, which operate in analogy to the swarming and social behavior found in nature, have been adopted to solve a variety of engineering problems. In this paper, an optimization strategy based on an improved bacterial foraging strategy based on Gaussian distribution is proposed. The validity of the algorithm is tested on the TEAM Workshop Benchmark Problem 22, and results are compared with standard and advanced particle swarm approaches, showing the effectiveness and robustness of the proposed approach.