Results 311 to 320 of about 10,510,472 (349)
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Gigaflops in linear programming
Operations Research Letters, 1996zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Irvin J. Lustig, Edward Rothberg
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The Discovery of Linear Programming
IEEE Annals of the History of Computing, 1984Around 1940, linear programming was an idea whose time had come. Accordingly, it was discovered three times, independently, between 1939 and 1947, but each time in a somewhat different form dictated by the special circumstances of that discovery. The first discovery was by L. V. Kantorovich, a Soviet citizen, the second was by T. C.
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Linear multiplicative programming
Mathematical Programming, 1992zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hiroshi Konno, Takahito Kuno
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Interior-point polynomial algorithms in convex programming
Siam studies in applied mathematics, 1994Written for specialists working in optimization, mathematical programming, or control theory. The general theory of path-following and potential reduction interior point polynomial time methods, interior point methods, interior point methods for linear ...
Y. Nesterov, A. Nemirovski
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Linear and Nonlinear Programming
International Series in Operations Research and Management Science, 2021D. Luenberger, Y. Ye
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Management Models and Industrial Applications of Linear Programming
, 1961An accelerating increase in linear programming applications to industrial problems has made it virtually impossible to keep abreast of them, not only because of their number and diversity but also because of the conditions under which many are carried ...
A. Charnes, W. Cooper
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1960
Linear programming models possess the interesting property of forming pairs of symmetrical problems. To any maximization problem corresponds a minimization problem involving the same data, and there is a close correspondence between their optimal solutions. The two problems are said to be “duals” of each other.
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Linear programming models possess the interesting property of forming pairs of symmetrical problems. To any maximization problem corresponds a minimization problem involving the same data, and there is a close correspondence between their optimal solutions. The two problems are said to be “duals” of each other.
openaire +2 more sources