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Bacterial foraging optimization (BFO) is a relatively new bio-heuristic algorithm which is based on a metaphor of social interaction of E. coli bacteria. Although the algorithm has successfully been applied to many kinds of real word optimization problems, experimentation with complex problems reports that the basic BFO algorithm possesses a poor performance. Thus a novel bacterial foraging optimizer with linear decreasing chemotaxis step (BFO-LDC) algorithm is proposed in the present paper. The performance of the proposed BFO-LDC is amply demonstrated by applying it for four classical test functions and comparing it with basic BFO. And the results obtained show this proposed algorithm greatly improves the efficiency of basic BFO algorithm.