A new algorithm for linear programming problems is presented. The algorithm makes interior moves with a special active set strategy that utilizes both local and global knowledge. This knowledge represents primarily monotonicity and dominance information. The article describes the rationale, theory, implementation, and some test examples for the algorithm. The ideas presented form the basis for nonlinear programming extensions in sequel articles.

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