The multiple attribute group decision-making problems with unknown experts' weights are studied. Based on the score and accuracy functions, the generalized distance measure is introduced to define a total order relation, which can distinguish arbitrary different dual hesitant fuzzy numbers. Then, in order to overcome the shortcomings of the existing operators, some new Hamacher operational laws are defined, and the adjusted dual hesitant fuzzy Hamacher weighted (A-DHFHW) operators are proposed, and the intrinsic relationship between the operators and the parameter is analyzed. To obtain the object weights of the experts, the optimization model is constructed by maximizing the distance measure-based group consensus. Furthermore, a new group decision making method is proposed based on total order relation, weight optimization model and the A-DHFHW operators. Finally, the effectiveness and practicability of the proposed group decision method are verified by solving the evaluation problem of the large data analysis platform, and the influence of the parameters on the decision results is analyzed.