simplex algorithm oor Sjinees
simplex algorithm
en
a method for solving problems in linear programming that tests adjacent vertices of the feasible set in sequence so that at each new vertex the objective function improves or is unchanged.
Vertalings in die woordeboek Engels - Sjinees
单纯形法
Geskatte vertalings
Vertoon algoritmies gegenereerde vertalings
voorbeelde
Advanced filtering
Voorbeelde moet herlaai word.
For this purpose, a simplex algorithm (SA) with random samplings is adopted in the optimization.
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Simplex algorithm - a method for solving optimisation problems with inequalities.
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important class of optimisation problem, and the simplex algorithm. Basically, one of the most important algorithms in practice.
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One of the first applications of the simplex algorithm was to the determination of an adequate diet that was of least cost.
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This module starts by introducing linear programming and the Simplex algorithm for solving continuous linear optimization problems, before showing how the method can be incorporated into Branch and Bound search for solving Mixed Integer Programs.
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Optimization toolbox Ready-to-use blocks with polynomial, least squares, and simplex optimization algorithms
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Some of the most important methods and algorithms of the 20th century are: the simplex algorithm , the Fast Fourier Transform , error-correcting codes , the Kalman filter from control theory and the RSA algorithm of public-key cryptography .
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For this, it is necessary to select the "Plastic capacity design" option in the General Data dialog box. In this design, the enlargement factor αplast is determined as the maximum of a linear optimization task in order to reach the plastic cross‐section resistance, taking into account the interaction conditions ("Revised Simplex Algorithm").
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This method keeps the points that still satisfy the initial restrictions. The above algorithm creates the vertices of the feasible region in the simplex defined by the factor constraints.
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9 sinne gevind in 4 ms. Hulle kom uit baie bronne en word nie nagegaan nie.