MIE376 Lec 3 - Revised Simplex.page1

# MIE376 Lec 3 - Revised Simplex.page1 - = 4 3 2 1 x x x x x...

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MIE376 Mathematical Programming Lecture Notes Daniel Frances © 2011 1 Lecture 3 Revised Simplex Method – Matrix Notation Before we showed how to solve problems by simple substitution; now we will deal with algorithms which more closely resemble how commercial codes perform the calculations. The notation introduced here is essential to be able to deal with the more advanced LP concepts of decomposition and column generation to be covered later in this course. Only the second box in the earlier flow chart is changed to: Back to the lathe example: Maximize z = x 1 +2*x 2 + 0*x 3 + 0*x 4 subject to x 1 + 3*x 2 + x 3 = 16 x 1 + x 2 +x4 = 7 x 1 , x 2 , x 3 , x 4 0 In Matrix form Max c T x s.t. Ax=b, x≥0 where
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Unformatted text preview: = 4 3 2 1 x x x x x = 2 1 c = 7 16 b = 1 1 1 1 3 1 A Let’s separate all the elements of the original problem into a basic and a non-basic part • the vector x will have the basic variables in a vector x B and the non-basic variables in x N • the vector c will have the coefficients of the basic variables in c B and the non-basic ones in c N None None Find an initial basic feasible solution Update the basis Update B-1 Identify the entering and departing variables entering variable? departing variable? Optimal solution Unbounded solution...
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