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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:

 

obj 4 x  5 y

 

constraints x0, y0,  x+2 y 6,  5 x+4 y 20

 

OptimizationLPSolveobj, constraints

19.00000,y=1.66667,x=2.66667

(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.

 


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