Examples of using Linear programming in English and their translations into Ukrainian
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What is the significance of duality theory of linear programming?
Linear programming is a special case of mathematical programming(mathematical optimization).
Translation of a series of articles“A set of tools for linear programming GNU”.
Linear programming is a specific flake of mathematical programming(mathematical optimization).
And why not stochastic processes, linear programming, or fluid simulation?
Linear programming is a special case of mathematical programming(also known as mathematical optimization).
One approach is to use special formulations of linear programming problems.
A closed feasible region of a linear programming problem with three variables is a convex polyhedron.
In this case, the initial task of the VP is replaced by a new, approximate problem,which is a linear programming problem.
A series of linear programming constraints on two variables produce a region of possible values for those variables.
GAMS idea is presented at the International Symposium on Mathematical Programming(ISMP), Budapest 1978 Phase I: GAMS supports linear programming.
For instance, linear programming déals with the case that both the objective function and the constraints are linéar.
In both cases, the equilibrium is determined by maximizing the total consumer andproducer surplus via linear programming.
For instance, linear programming deals with the case that both the objective function and the constraints are linear. .
Many multi-agent pathfinding algorithms are generalized from A*, or based on reduction to otherwell studied problems such as integer linear programming.
Quantum logic, theory of business games, linear programming and mathematical statistics are just part of what he“gifted” to science.
In order to solve the specified tasks, the article built optimisation models,which correspond with setting mathematical tasks of partially integer-valued linear programming.
In a linear programming problem, a series of linear constraints produce a convex feasible region of possible values for those variables.
This usage is the same as that in the phrases linear programming and mathematical programming, a synonym for optimization.[4].
A linear programming algorithm finds a point in the polytope where this function has the smallest(or largest) value if such a point exists.
For implicit scheme the anti-diffusion flux-limitation problem is reduced to non-linear programming problem orsequence of the linear programming problems.
A linear programming algorithm perceives a point in the polyhedron where this purpose has the smallest or largest value if such a point endures.
Computer Mathematics combines the fields of mathematics and technology through courses such as logic and information,applications of analysis, linear programming and statistics.
A linear programming algorithm finds a point within the polyhedron the place this function has the smallest(or largest) worth if such a degree exists.
Professor Martin Groetschel observed that a linear programming problem that would take 82 years to solve in 1988 could be solved in one minute in 2003.
In linear programming problems, the feasible set is a convex polytope: a region in multidimensional space whose boundaries are formed by hyperplanes and whose corners are vertices.
Most rely on linear programming(including mixed-integer programming), although some use nonlinear programming. .
Beginning of linear programming was initiated in 1939 by the Soviet mathematician and economist Kantorovich in his paper"Mathematical methods of organizing and planning production.".
Since the approximate problem(10.13) is a linear programming problem and we usually solve it by the simplex method, the conditions for the non-negativity of the variables are written separately from the remaining constraints.