Abstract: Focusing on the disadvantages that Grey Wolf Optimizer (GWO) was easy to fall into local optimum and had bad local searching ability on optimization, local search strategy and diversity maintenance strategy were proposed. On the basis of that, the Grey Wolf Optimizer Based on Tent Chaotic Sequence (TCGWO) was established. The local searching ability could be improved by local search strategy; falling into local optimum could be avoided by diversity maintenance strategy. 23 benchmark test functions were used to experiment and analysis, and comparative analysis with GWO, Flower Pollination Algorithm (FPA) and Artificial Bee Colony Algorithm (ABC). According to the result, TCGWO is effective and superior.