2.1. Generalized simplex method
The simplex method has been very successful in solving LP problems [10,11]. It was invented by George B.
Dantzig in the summer of 1947. The first significant application is that Laderman solved a diet-planning problem
with nine equality constraints and 27 non-negative variables [12]. Before the simplex method can be used
to solve a LP problem, the constraint set must be converted into the equivalent form in which all constraints
are equations and all variables are non-negative. This is the so-called standard form [5]. In order to convert
into standard form, each inequality constraint must be replaced by an equality constraint. If the ith constraint
of the problem set is 6, we convert it to an equality constraint by adding a slack variable si to the ith constraint
and adding another restriction si P 0. In contrast to this, if the jth constraint of the problem set is P, it will be
converted to an equality constraint by subtracting an excess variable ei to the jth constraint and adding
another restriction ei P 0. Then consider the LP problem in standard form (see [8] for more details):
maximize z ¼ CX
subject to
AX ¼ b; X P 0