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History of Mathematical Programming Systems [Back Matter]

IP.com Disclosure Number: IPCOM000129452D
Original Publication Date: 1984-Jul-01
Included in the Prior Art Database: 2005-Oct-06
Document File: 23 page(s) / 94K

Publishing Venue

Software Patent Institute

Related People

WILLIAM ORCHARD-HAYS: AUTHOR [+2]

Abstract

The systematic development of practical computing methods for linear programming (LP) began in 1952 at the Rand Corporation in Santa Monica, under the direction of George B. Dantzig. The author worked intensively on this project there until late 1956, by which time great progress had been made on first-generation computers. The work continued at CEIR, Inc., in Washington for some years and later in many places by many individuals and firms. By the late 1960s, elaborate systems of programs known as mathematical programming systems (MPS) had become a standard part of the available software for a number of computers, notably the IBM 360, GE 635, CDC 6600, and Univac 1108. The major MPSS underwent significant updating and extension during the mid-1970s, taking on their present and probably final form, at least for big mainframes. Work still continues, however, and substantial improvements are being made in speed, reliability, supporting data management and control systems, and application techniques. Development of quite powerful microcomputer systems is now underway.

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THIS DOCUMENT IS AN APPROXIMATE REPRESENTATION OF THE ORIGINAL.

Copyright ©; 1984 by the American Federation of Information Processing Societies, Inc. Used with permission.

History of Mathematical Programming Systems [Back Matter]

WILLIAM ORCHARD-HAYS

(Image Omitted: © 1984 by the American Federation of Information Processing Societies, Inc. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the AFIPS copyright notice and the title of the publication and its date appear, and notice is given that the copying is by permission of the American Federation of Information Processing Societies, Inc. To copy otherwise. or to republish, requires specific permission. Author's Address: Energy Information Administration,
L.S. Department of Energy, EI522 Mail Stop 2F-021, Washington, DC 20585. © 1984 AFIPS 0164-1239/84/030296-312

History of Mathematical Programming Systems [Back Matter]

WILLIAM ORCHARD-HAYS .00/00)

The systematic development of practical computing methods for linear programming (LP) began in 1952 at the Rand Corporation in Santa Monica, under the direction of George B. Dantzig. The author worked intensively on this project there until late 1956, by which time great progress had been made on first-generation computers. The work continued at CEIR, Inc., in Washington for some years and later in many places by many individuals and firms. By the late 1960s, elaborate systems of programs known as mathematical programming systems (MPS) had become a standard part of the available software for a number of computers, notably the IBM 360, GE 635, CDC 6600, and Univac 1108. The major MPSS underwent significant updating and extension during the mid-1970s, taking on their present and probably final form, at least for big mainframes. Work still continues, however, and substantial improvements are being made in speed, reliability, supporting data management and control systems, and application techniques. Development of quite powerful microcomputer systems is now underway.

Categories and Subject Descriptors: G. 1.6 [Numerical Analysis]: Optimization; K.2 [History of Computing] -- people, software General Terms: Theory

Foreword

George B. Dantzig

The two papers, Doriman's on the "discovery" of linear programming and this one on its development as a computational science, are two sides of the same coin. Linear programs are among the largest mathematical systems solved -- routinely systems of thousands of equations and variables are solved in a few minutes on modern large computers. When we stop to consider that what is being solved is not some large square system but a combinatorial problem of great complexity, the achievement becomes most remarkable. The ingredients that have made it possible for humans to come to grips -- for the first time in history -- with some aspects of decision making in complex economies and industry are faster and...