The Evolution of Mathematical Programming Systems

Computer programs to solve linear programming problems by the simplex method have existed since the early 1950s. They remain the central feature of today's mathematical programming systems. There has been a steady increase in the size of problem that can be solved: this has been due as much to a better understanding of how to exploit sparseness as to larger and faster computers. There has been a steady increase in the type of problem that can be solved: this has been due as much to new concepts, such as separable programming, integer variables and special ordered sets, as to new algorithms. There has been a steady increase in the extent to which the application of mathematical programming has become more automatic. This applies both to the use of computerized matrix generators and report writers and to the mathematical formulation itself, in that we rely less on the user producing a well-scaled linear programming problem and are starting on the process of automatically sharpening the formulation of integer programming problems.Important new work is being done on all these aspects of computational mathematical programming.

[1]  G. Dantzig,et al.  Notes on Linear Programming: Part 1. The Generalized Simplex Method for Minimizing a Linear Form under Linear Inequality Restraints , 1954 .

[2]  G. Dantzig,et al.  THE PRODUCT FORM FOR THE INVERSE IN THE SIMPLEX METHOD , 1954 .

[3]  G. Dantzig UPPER BOUNDS, SECONDARY CONSTRAINTS, AND BLOCK TRIANGULARITY IN LINEAR PROGRAMMING , 1955 .

[4]  H. Markowitz The Elimination form of the Inverse and its Application to Linear Programming , 1957 .

[5]  A. S. Manne,et al.  On the Solution of Discrete Programming Problems , 1956 .

[6]  George B. Dantzig,et al.  Decomposition Principle for Linear Programs , 1960 .

[7]  R. E. Griffith,et al.  A Nonlinear Programming Technique for the Optimization of Continuous Processing Systems , 1961 .

[8]  G. Zoutendijk,et al.  Methods of Feasible Directions , 1962, The Mathematical Gazette.

[9]  George B. Dantzig,et al.  Linear programming and extensions , 1965 .

[10]  E. M. L. Beale,et al.  Experiences in Using a Decomposition Program , 1965, Comput. J..

[11]  George B. Dantzig,et al.  Generalized Upper Bounding Techniques , 1967, J. Comput. Syst. Sci..

[12]  E. M. L. Beale,et al.  Mathematical programming in practice , 1968 .

[13]  G. Ribiere,et al.  Experiments in mixed-integer linear programming , 1971, Math. Program..

[14]  Eli Hellerman,et al.  Reinversion with the preassigned pivot procedure , 1971, Math. Program..

[15]  James E. Kalan Aspects of large-scale in-core linear programming , 1971, ACM '71.

[16]  John A. Tomlin,et al.  Updated triangular factors of the basis to maintain sparsity in the product form simplex method , 1972, Math. Program..

[17]  Paula M. J. Harris Pivot selection methods of the Devex LP code , 1973, Math. Program..

[18]  Gautam Mitra Investigation of some branch and bound strategies for the solution of mixed integer linear programs , 1973, Math. Program..

[19]  John J. H. Forrest,et al.  Practical Solution of Large Mixed Integer Programming Problems with Umpire , 1974 .

[20]  L. Schrage Implicit representation of variable upper bounds in linear programming , 1975 .

[21]  Gautam Mitra,et al.  Analysis of mathematical programming problems prior to applying the simplex algorithm , 1975, Math. Program..

[22]  E. M. L. Beale,et al.  Global optimization using special ordered sets , 1976, Math. Program..

[23]  Michel Bénichou,et al.  The efficient solution of large-scale linear programming problems—some algorithmic techniques and computational results , 1977, Math. Program..

[24]  Wm. Orchard-Hays Anatomy of a Mathematical Programming System , 1978 .

[25]  H. P. Williams,et al.  Model Building in Mathematical Programming , 1979 .

[26]  Leon S. Lasdon,et al.  The Status of Nonlinear Programming Software , 1979, Oper. Res..

[27]  A. Land,et al.  Computer Codes for Problems of Integer Programming , 1979 .

[28]  John K. Reid,et al.  A sparsity-exploiting variant of the Bartels—Golub decomposition for linear programming bases , 1982, Math. Program..

[29]  L. Lasdon,et al.  Nonlinear Optimization by Successive Linear Programming , 1982 .

[30]  H. C. Williams,et al.  Advanced Linear Programming , 1983, The Mathematical Gazette.

[31]  James K. Ho,et al.  Computational experience with advanced implementation of decomposition algorithms for linear programming , 1983, Math. Program..

[32]  John A. Tomlin,et al.  Formal optimization of some reduced linear programming problems , 1983, Math. Program..

[33]  Ellis L. Johnson,et al.  Solving Large-Scale Zero-One Linear Programming Problems , 1983, Oper. Res..

[34]  William Orchard-Hays History of Mathematical Programming Systems , 1984, Annals of the History of Computing.