linear programming oor Grieks
linear programming
en
(mathematics) the branch of mathematics concerned with the minimization or maximization of a linear function of several variables and inequalities; used in many branches of industry to minimize costs or maximize production
Vertalings in die woordeboek Engels - Grieks
γραμμικός προγραμματισμός
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Von Neumann's algorithm was the first interior point method of linear programming.
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Operations research techniques include linear programming and other areas of optimization, queuing theory, scheduling theory, network theory.
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Defining polyhedra in this way provides a geometric perspective for problems in linear programming.
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He is regarded as the founder of linear programming.
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Industries that use linear programming models include transportation, energy, telecommunications, and manufacturing.
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Linear programming can be applied to various fields of study.
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Von Neumann's results have been viewed as a special case of linear programming, where von Neumann's model uses only nonnegative matrices.
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Examples include Gaussian elimination, the QR factorization method for solving systems of linear equations, and the simplex method of linear programming.
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Convex polytopes play an important role both in various branches of mathematics and in applied areas, most notably in linear programming.
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In the Bicol region of the Philippines, researchers brought in a computer to examine the program, using what is called “Linear Programming.”
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More formally, linear programming is a technique for the optimization of a linear objective function, subject to linear equality and linear inequality constraints.
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He came up with the mathematical technique now known as linear programming in 1939, some years before it was advanced by George Dantzig.
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Later, von Neumann suggested a new method of linear programming, using the homogeneous linear system of Gordan (1873), which was later popularized by Karmarkar's algorithm.
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Then, Dantzig listened dumbfounded while von Neumann provided an hour lecture on convex sets, fixed-point theory, and duality, conjecturing the equivalence between matrix games and linear programming.
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Nobel prize lecture Kantorovich, Leonid, "Mathematics in Economics: Achievements, Difficulties, Perspectives", Nobel Prize lecture, December 11, 1975 "Autobiography: Leonid Kantorovich", Nobel Prize website Dantzig, George, Linear programming and extensions.
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Several authors have made conjectures that imply that the fractional chromatic index of any multigraph (a number that can be computed in polynomial time using linear programming) is within one of the chromatic index.
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In addition, as far as non-linear programming is concerned, it will be necessary to examine whether specific rules are required, notably with the aim of guaranteeing the separation between editorial content and commercial messages.
ΤΙ ΣΥΜΒΑΙΝΕΙ ΜΕ ΤΙΣ ΑΙΤΗΣΕΙΣ ΠΟΥ ΠΑΡΑΛΑΜΒΑΝΟΝΤΑΙEurLex-2 EurLex-2
development, use and maintenance of partial equilibrium models of energy systems and sectors as well as multi-regional, multi-time-period, geographic information system (GIS) and linear programming models of energy technology and infrastructure capacity expansion
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development, use and maintenance of partial equilibrium models of energy systems and sectors as well as multi-regional, multi-time-period, geographic information system (GIS) and linear programming models of energy technology and infrastructure capacity expansion
Ελεύθερη λειτουργία σύμφωνα με την παράγραφο #.#.#. του προσαρτήματος # του παραρτήματος #: ναι/ όχιoj4 oj4
Linear television programming and broadcasting services
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Building on his results on matrix games and on his model of an expanding economy, von Neumann invented the theory of duality in linear programming, after George Dantzig described his work in a few minutes, when an impatient von Neumann asked him to get to the point.
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Linear and emulation programming, development of software packages for human resources management, optimisation and planning
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Approximate confidence limits may be obtained with standard non-linear regression programs with re-parameterisation (Bruce and Versteeg, 1992), which involves rewriting the mathematical equation with the desired point estimates, e.g. the EC10 and the EC50 as the parameters to be estimated.
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