  The problem of optimizing a linear objective function,given a number of
linear constraints has been a long standing problem ever since the times of
Kantorovich, Dantzig and von Neuman. These developments have been followed by a
different approach pioneered by Khachiyan and Karmarkar.
  In this paper we present an entirely new method for solving an old
optimization problem in a novel manner, a technique that reduces the dimension
of the problem step by step and interestingly is recursive. A theorem which
proves the correctness of the approach is given.
  The method can be extended to other types of optimization problems in convex
space, e.g. for solving a linear optimization problem subject to nonlinear
constraints in a convex region.
