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Lightweight Presentation Protocol (LPP) is a protocol used to provide ISO presentation services on top of TCP/IP based protocol stacks. It is defined in RFC 1085. The Lightweight Presentation Protocol describes an approach for providing "streamlined" support of OSI model-conforming application services on top of TCP/IP-based network for some constrained environments.
The linear programming problem is to find a point on the polyhedron that is on the plane with the highest possible value. Linear programming ( LP ), also called linear optimization , is a method to achieve the best outcome (such as maximum profit or lowest cost) in a mathematical model whose requirements and objective are represented by linear ...
In mathematical optimization, the fundamental theorem of linear programming states, in a weak formulation, that the maxima and minima of a linear function over a convex polygonal region occur at the region's corners.
The use of randomization to improve the time bounds for low dimensional linear programming and related problems was pioneered by Clarkson and by Dyer & Frieze (1989). The definition of LP-type problems in terms of functions satisfying the axioms of locality and monotonicity is from Sharir & Welzl (1992) , but other authors in the same timeframe ...
In order to use Dantzig–Wolfe decomposition, the constraint matrix of the linear program must have a specific form. A set of constraints must be identified as "connecting", "coupling", or "complicating" constraints wherein many of the variables contained in the constraints have non-zero coefficients.
Multi-objective linear programming is a subarea of mathematical optimization. A multiple objective linear program (MOLP) is a linear program with more than one objective function. An MOLP is a special case of a vector linear program .
Today's NYT Connections puzzle for Tuesday, December 10, 2024The New York Times
There is a close connection between linear programming problems, eigenequations, and von Neumann's general equilibrium model. The solution to a linear programming problem can be regarded as a generalized eigenvector. The eigenequations of a square matrix are as follows: