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About 10,000 papers for “Linear programming”

Linear Programming and Integer Linear Programming

Kurt Mehlhorn · 2013

Cited by 0

Mathematical Programming, Linear Programming

Lin Wang · 2013

Cited by 0

Linear Programming An Introduction to Linear Programming

Mit Opencourseware · 2011

Linear programming is a very important class of problems, both algorithmically and combinatorially. Linear programming has many applications. From an algorithmic point-of-view, the simplex was proposed in the forties (soon after the war, and was motivated by military applications) and, although it has performed very well in practice,

Cited by 0

Linear Programming

Giorgio Giorgi, Bienvenido Jiménez, Vicente Novo · 2025

Cited by 0

Linear Programming

Raúl Poler, Josefa Mula, Manuel Díaz‐Madroñero et al. · 2025

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Linear Programming

Mark de Berg, Otfried Cheong, Marc van Kreveld et al. · Computational Geometry · 2008

Cited by 1

Linear Programming

R. Fletcher · 2000

Cited by 0

Linear Programming

Calhoun: The Naval Postgraduate School Institutional Archive (Naval Postgraduate School) · 2004

Interactive Media Element

Cited by 0

LINEAR PROGRAMMING

Martin Dyer, Nimrod Megiddo, Emo Welzl · 1997

Cited by 0

Linear Programming

Masatoshi Sakawa, Hitoshi Yano, Ichiro Nishizaki · RePEc: Research Papers in Economics

Abstract Since G.B. Dantzig first proposed the simplex method around 1947, linear programming, as an optimization method of maximizing or minimizing a linear objective function subject to linear constraints, has been extensively studied and, with the significant advances in computer technology, widely used in the fields of operations research, industrial engineering, systems science, management science, and computer science.

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Linear Programming

Fuad Aleskerov, Hasan Ersel, Dmitri Piontkovski · RePEc: Research Papers in Economics

Abstract The linear programming problem is a general problem of finding the maximal value of the function f(x) = (a, x), where $$\mathbf{x} \in {\mathbb{R}}^{n}$$ is a vector of n unknowns and $$\mathbf{a} \in {\mathbb{R}}^{n}$$ is a constant vector, under the restrictions $$\mathbf{x} \geq \mathbf{0}\mbox{ and }A\mathbf{x} \geq \mathbf{d}, $$ where A is a matrix and d is a constant vector. This problem has a lot of applications to economic models and practice. Some simple and rather artificial applications are discussed below. In mathematical terms the problem is maximizing a linear objective function under linear constraints where the relevant variables are restricted to be non-negative. It was first solved by Kantorovich.

Cited by 0

Linear Programming

D. Goldfarb, M. Todd · eCommons (Cornell University) · 1988

Linear Programming

Cited by 0Open access