IntroductionThe algorithm, which will be described in the following pages, in many cases takes fewer iteration steps and less time to solve a linear programming problem than the simplex algorithm.The essential idea of the Duoplex-Method is as follows: In many cases a constraint can be determined by simple calculations in such a manner that the optimum of the objective function is assumed on it. The hyperplane corresponding to this constraint is then introduced as a new coordinate plane.Taking into consideration only points on this plane, the solution of the linear programming problem can be accomplished by a slight modification of the simplex algorithm.There are cases in which the constraint, determined by the first step of the algorithm, does not contain the optimum (see examples t and 3). Moreover, in these cases the algorithm is finite but may take more iteration steps than the simplex algorithm.
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