Dual variables are also known as shadow prices or Lagrange multipliers. They represent the change in the optimal value of the objective function when the right-hand side of a constraint is ...

The dual simplex method is a powerful technique used to solve linear programming problems by optimizing ... and assign them zero values. The nonbasic variables are then assigned the values of ...

We present two first-order primal-dual algorithms for solving saddle point formulations of linear programs, namely FWLP (Frank-Wolfe Linear Programming) and FWLP-P. The former iteratively applies the ...

In this paper, we develop a novel approach namely the primal-dual simplex algorithm to overcome mentioned shortcomings. A numerical example is given to illustrate the proposed approach. [1] K. Ganesan ...

Google researchers introduce PDLP (Primal-Dual Hybrid Gradient enhanced for Linear Programming), a new solver built on the restarted PDHG algorithm. PDLP uses matrix-vector multiplication instead of ...

In this paper, we present a modified dual of the standard linear program that guarantees ... we then derive novel dual forms of dynamic programming, including policy evaluation, policy iteration and ...

With this approach, Delsarte constructs a linear program such that its maximum value is an upper bound on the maximum size of a code with a given minimum distance. Bounding this value can be done by ...

problems involving symmetric trapezoidal fuzzy numbers without converting them to crisp linear programming problems are the fuzzy primal simplex method proposed by Ganesan and Veeramani [1] and the ...