Primal interior dual-simplex method and dual interior primal-simplex method in the general bounded linear programming

In this paper, Primal-Interior Dual-Simplex method (PIDS) and Dual-Interior Primal-Simplex method (DIPS) are developed for the general bounded linear programming. Two methods were implemented and compared with other pricing techniques for the Netlib linear programming problems: For the PIDS, the present approach shows superior performance to both most negative rule and dual steepest-edge method since it practically reduces degenerate iterations and has property to reduce the problem. For the DIPS, it requires less iterations and computational time than least reduced cost method, but it shows inferior performance to the dynamic primal steepest-edge method.