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Optimization: Linear Programming

Maple is able to solve linear optimization problems with hundreds of variables and constraints. Problem types that are covered include continuous, integer, mixed-integer, and binary linear programs.

This example illustrates the functionality on a simple linear system:

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 $\left[{-}{19.00000}{,}\left[{y}{=}{1.66667}{,}{x}{=}{2.66667}\right]\right]$ (1.1)

This is a very small example, but Maple is able to deal with very large systems, specified either in equation notation or in matrix form.