George B. Dantzig

November 8, 1914 – May 13, 2005

Brief Biography


Celebrated as the “Father of Linear Programming”, George Dantzig was born to Latvian-American mathematician Tobias Dantzig and French linguist Anja Dantzig (née Ourisson). The younger Dantzig originally struggled with mathematics in school before discovering an interest in geometry. He received his undergraduate degree from the University of Maryland, College Park and earned his masters on a graduate scholarship from the University of Michigan, Ann Arbor.

After receiving his master's degree, George Dantzig worked for the US Bureau of Labor Statistics before serving during World War II as Chief of the Combat Analysis Branch of the Statistical Control Division of the United States Army Air Forces. Following the war, he received his doctorate from the University of California, Berkeley under Jerzy Neyman and worked as a mathematician on Project SCOOP (Scientific Computation of Optimal Programs) in the Office of the Comptroller of the U. S. Air Force. At SCOOP, he worked closely with Murray Geisler who would later work with him at RAND.

He was challenged by colleagues at the Pentagon to work out a method the Air Force could employ to quicken and mechanize its planning process. It was while doing this work that he developed the linear programming model and the simplex algorithm to solve it.  In Dantzig’s model, “programming” refers to planning, and “linear” to the proportional and additive relationship between activities and the resources they consume and costs they incur.  The simplex algorithm is a technique to compute the optimal combination from among a potentially large number of possible activities. (Unbeknownst to Dantzig and most other operations researchers in the West, a similar method was derived eight years prior by Soviet mathematician Leonid V. Kantorovich)

Dantzig showed that thousands of decision problems across varying fields of business, government, and the military could be formulated as linear programming problems. Linear programming gave operations researchers a means to address preexisting and new problems in OR. It also presented a novel methodology of deriving and finding mathematical proofs.  

Dantzig went on to join the RAND Corporation before becoming the Professor of Operations Research and Chairman of the Operations Research Center at the University of California, Berkeley in 1960. Early on he developed the decomposition principle with Philip Wolfe . It is an algorithm that solves linear programming and relies on delayed column generation for improving the tractability to larger linear programs. In 1966 he joined Stanford University where he remained as Professor of Operations Research and Computer Science, Co-Director of the Systems Optimization Laboratory (SOL), and Director of the PILOT Energy-Economic Model Project. The objective or SOL was the development of “computational methods and associated computer routines for numerical analysis and optimization of large-scale systems.” Dantzig went on to work with many of his students, including Richard W. Cottle.

Dantzig was member of the National Academy of Engineering, the National Academy of Science, and the American Academy of Arts and Sciences. He received the National Medal of Science along with eight honorary degrees. Dantzig's seminal work laid the foundation for much of systems engineering and is widely used in network design and component design in computational, mechanical, and electrical engineering. His work inspired the formation of the Mathematical Programming Society (now the Mathematical Optimization Society) and a major section of the Society for Industrial and Applied Mathematics (SIAM). Generations of Dantzig's students have become leaders in all facets of society.

In 1975 Tjalling Koopmans and Leonid Kantorovich were awarded the Nobel Prize in Economics for their contribution in resource allocation and linear programming. Many professionals, Koopmans and Kantorovich included, were surprised at Dantzig’s exclusion as an honoree. Most individuals familiar with the situation considered him to be just as worthy of the prize. Since 1994, The George B. Dantzig Award has been given annually by INFORMS for the best dissertation in any area of operations research and the management sciences.  He died in 2005 at the age of ninety.

Other Biographies

Profiles in Operations Research: George B. Dantzig
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Wikipedia Entry for George Dantzig

Cottle RW, Johnson E., & Wets R. (2007) George B Dantzig. in The American Mathematical Society Notice, 54(3), 344-362. (link)

Cottle RW (2008) George Dantzig at RAND, Berkeley, and Stanford. Presented Oct 14, 2008 


Gill P. E., Murray W., Saunders M. A., Tomlin J. A., & Wright M. H. (2008) George B. Dantzig and systems optimization. in Discrete Optimization, 5(2), 151-158. (link)

Gass, S. I. (2003) IFORS' Operational Research Hall of Fame: George B. Dantzig. International Transactions in Operations Research, 10 (2): 191-193. (link)


University of Maryland, A.B 1936

University of Michigan, MA 1939

University of California Berkeley, PhD 1946 (Mathematics Genealogy)


Academic Affiliations
Non-Academic Affiliations

Key Interests in OR/MS

Application Areas

Oral Histories

Interview of George Dantzig at his home in Stanford, California, by Irv Lustig (then with ILOG), March 5, 2001.

NOTE: The video chapter transcripts are searchable, with search results displayed as marks on the time bar above the search box.  Click a mark to jump to the search word or phrase in the video and transcript, or click on any word in the transcript to jump to that point in the video.

Jump to Chapters

Chapter 1: Beginnings of Linear Programming
Chapter 2: Early Applications and The First Solved Linear Program
Chapter 3: Programming, Optimization and Objective Functions
Chapter 4: Early Collaborations and Symposium Zero
Chapter 5: The Field of Optimization
Chapter 6: The Diet Problem and Anne Dantzig
Chapter 7: My Parents
Chapter 8: Awards
Chapter 9: Planning Under Uncertainty

Albers D. J. & Reid C. (1986) An Interview with George B. Dantzig, The Father of Linear Programming. The College Mathematics Journal 17: 292-314. (link)

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