ABSTRACT
Carter, Michael, “Linear Programming with Mathematica” in Computational Economics and Finance: Modeling and Analysis with Mathematica, edited by Hal R. Varian, New York: Springer, 1996
Chvátal, Vašek, Linear Programming, New York: Freeman, 1983
Dantzig, George B., Linear Programming and Extensions, Princeton, New Jersey: Princeton University Press, 1963
Dantzig, George B. and Mukund N. Thapa, Linear Programming, vol. 1: Introduction, New York: Springer, 1997
Dorfman, Robert, Paul A. Samuelson and Robert M. Solow, Linear Programming and Economic Analysis, New York: McGraw Hill, 1958
Garfinkel, Robert S. and George L. Nemhauser, Integer Programming, New York: Wiley, 1972
Nemhauser, G.L., A.H.G. Rinnooy Kan and M.J. Todd (editors), Optimization, Amsterdam: North Holland, 1989
Roos, C., T. Terlaky and J.-Ph. Vial, Theory and Algorithms for Linear Optimization: An Interior Point Approach, Chichester and New York: Wiley, 1997
Williams, H.P., Model Building in Mathematical Programming, 3rd edition, Chichester and New York: Wiley, 1990
The formulation, in 1947, of the simplex algorithm for solving linear programs ranks as one of the most significant discoveries of the 20th century. Fortuitously, the algorithm was conceived at the same time as the development of electronic computers. For the first time, it became practical to pose and solve large-scale optimization problems. The demand for optimization originated with defence forces in the aftermath of World War II. The potential of this new tool was soon recognized by business, which rapidly and profitably adopted it in the oil, food-processing, and steel industries for production and distribution planning. It also sparked whole new fields of study, such as mathematical programming and operations research.