An Active Set Algorithm of Conjugate Gradients for Adjustment Model with Interval Constraints

This paper mainly studies the adjustment model with interval constraints, in which the adjustment problem is transformed into a quadratic programming problem with interval constraints. A new adjustment algorithm with interval constraints is presented, and the accuracy of the parameter solution is evaluated, in which the active set algorithm and unconstrained conjugate gradient optimization algorithm are used to partition and reconstruct the quadratic problems. Because the projection gradient method can rapidly change the composition of the active constraint set, the new algorithm is more efficient than the classical active set method, which can reduce the uncertainty of the model, and maintain the statistical, geometric or physical meaning of priori information, and is suitable for solving large-scale adjustment problems with interval constraints.