PART I - BASIC THEORY AND METHOD: Linear programs and their solution; The simplex method. PART II - PRACTICAL ASPECTS: Problem setup; The basis matrix - fundamentals of numerical computation and numerical linear algebra; The basis matrix - factorising and solving; The basis matrix - updating and solving; Selection strategies - choosing the entering and exiting variables; Selection strategies - finding an initial feasible solution; Practical implementation;
Mathematical programming systems in practice. PART III - OPTIMIZATION PRINCIPLE + SIMPLEX METHOD = LP ALGORITHM: The duality principle and the simplex method; The decomposition principle and the simplex method; The homotopy principle and the simplex method; Bibliography; Index.