Efficient interior-point algorithm for solving the general non-linear programming problems
Efficient interior-point algorithm for solving the general non-linear programming problems
An Interior-point algorithm with a line-search globalization is proposed for solving the general nonlinear programming problem. At each iteration, the search direction is obtained as a resultant of two orthogonal vectors. They are obtained by solving two square linear systems. An upper-triangular linear system is solved to obtain the Lagrange multiplier vector. The three systems that must be solved each iteration are reduced systems obtained using the projected Hessian technique. This fits well