Revised Simplex Method: An Efficient Approach to Linear Programming, Slides of Operational Research

A detailed explanation of the revised simplex method, an efficient approach to solving linear programming problems. The basic ideas, formulas, and steps involved in the method, including the initialization, pivot selection, and optimality test. It also discusses the importance of updating the b-1 matrix and the role of the method in large sparse lp problems.

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2012/2013

Uploaded on 01/09/2013

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Revised Simplex Procedure
Basic Ideas:
Update B-1 matrix by pivoting (as usual)
Compute any other column that you need
on the fly, i.e.
new column =B-1 initial column
Update the reduced costs by the formula
r = cBB-1D - c
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Revised Simplex Procedure

Basic Ideas :

Update B -1^ matrix by pivoting (as usual) Compute any other column that you need on the fly, i.e. new column =B-1^ initial column Update the reduced costs by the formula r = c (^) BB -1^ D - c

The Formulas Revisited

rD c (^) B B D (^) I cD D

= −^1. −

D .'^ j = B −^1 D. j

b ' = B −^1 b

xB = B −^1 b

x (^) D = (0,...,0)

Z = cB x (^) B

c = Original cost vector

Step 1: Initialisation

ID = (1,2) ; IB =(3,4,5) ; B -1=I

BV Eq. # Z (^) x 1 x 2 x 3 x 4 x 5 RHS

x 3 1 0 2 1 1 0 0 40 x 4 2 0 1 1 0 1 0 30 x 5 3 0 1 0 0 0 1 15 Z Z (^1) − 4 − 3 0 0 0 0

Step 2:(stop?)

The are negative reduced costs so we

continue

Step 3:(Variable in)

Using the Greedy Rule, we select x 1 as the

new basic variable.

Step 4: (Variable out)

Applying the Ratio Test we take x 5 out of the

basis.

Step 5:(Update the indices I (^) B and I (^) D ,etc)

Step 6: Update B -

In contrast to the Primal Simplex Method,

here we do not update the entire simplex tableau. The main update is the B -1^ section of the tableau.

We use the usual pivot operation for this

purpose.

BV Eq. # (^) x 1 x 2 x 3 x 4 x 5 RHS

x 3 1 1 0 - 2 x 4 2 0 1 - 1 x 1 3 0 0 1 Z Z

In practice, when we update B -1^ we also update the RHS and the z-row elements under the B -1^ matrix (why?)

Step 8: Variable in

The first non-basic variable is selected by the

Greedy Rule

Since I (^) D = (2,5), this is x 2.

D ⋅ 2

' = B

− 1 D ⋅ 2 =

b ' = B

− 1 b =

Step 9: Variable out

Step 5: Update

IB = (2,4,1) ; ID = (3,5), etc

BV Eq. #

x 1 x 2 x 3 x 4 x 5 x 3 RHS x 4 1 1 0 −^2 x 1 2 0 1 −^1 3 0 0 1 15 Z Z

D = S. I D =

cB = c (^) I (^) B = (3,0, 4)

Correction:

D ⋅ 2

'

BV Eq. # (^) x 1 x 2 x 3 x 4 x 5 RHS

x (^2 1 1 0) - 2 x 4 2 - 1 1 1 x 1 3 0 0 1 Z Z

New B -

Step 7: Optimality Test

There is a negative reduced cost so we continue

rD = c (^) B B −^1 Dc (^) D = (3,0, 4)

1 0 − 2 − 1 1 1 0 0 1

  

  

1 0 0

0 0 1

  

  

− (0,0) = (3, −2)

Step 9: Variable Out

We have to perform the Ratio Test on column

  1. Since this column is part of B -1, we do not have to compute it from scratch. It is part of the updated B -1.

b ' = B

− 1 b =

D = SI (^) D =

1

0

0

0

0

1

  

  

D ⋅' 5 =

− 2

1

1

  

  