  We introduce an algorithm which can be directly used to feasible and optimum
search in linear programming. Starting from an initial point the algorithm
iteratively moves a point in a direction to resolve the violated constraints.
At the same time, it ensures that previously fulfilled constraints are not
breached during this process. The method is based on geometrical properties of
n-dimensional space and can be used on any type of linear constraints (>, =,
$\geq$), moreover it can be used when the feasible region is
non-full-dimensional.
