Abstract In this paper,based on the least square adjustment criterion, the ill-posed adjustment problem is transformed into an unconstrained quadratic programming problem. At the same time, the influence of ill-posed problems on the solution of the adjustment is analyzed by using optimization theory. The conjugate gradient search algorithm is used to find the optimal step size factor in the feasible region and automatically ascertain the steepest descent direction. The setting method of iterative initial value is given, and we analyze the relationship between ill-posed problems and local optimal solutions in approximate calculation, which gives a fast-iterative method of local optimal solution. We also analyze the validity of the algorithm and the speed of iteration through two examples. The algorithm can be used to deal with the highly ill-posed adjustment problem of large-scale coefficient matrices becausethe inverse matrix about the coefficient matrix of normal equation is not calculated in the whole calculation process.