On the probabilistic complexity of finding an approximate solution for linear programming

We consider the problem of finding an $\epsilon-$optimal solution of a standard linear program with real data, i.e., of finding a feasible point at which the objective function value differs by at most $\epsilon$ from the optimal value. In the worst-case scenario the best complexity result to date guarantees that such a point is obtained … Read more