A multiple attribute decision making problem under hesitant fuzzy environment with unknown weight information is investigated. The ranking results of alternatives are affected when adding elements into a hesitant fuzzy element(HFE). To overcome this drawback, a signed distance-based approach for the multiple attribute decision making with hesitant fuzzy information is proposed. Firstly, a novel hesitancy index based on the number and deviation of elements in a HFE is presented, and a hesitant fuzzy signed distance measure is proposed. Then, an optimization model on the basis of the signed distance measure is constructed to determine the attribute weights, and the priorities of alternatives can be obtained. Finally, a numerical example is given to illustrate the rationality and effectiveness of the proposed method.