Simplex Method for Linear Programming Problems: Limitations and Exceptions

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In summary: L_1'=L_1+ \frac{1}{2}L_2' \\ P_2 &... & 0 & 1 & -\frac{1}{2} & 0 & \frac{1}{2} & 0 & & L_2'=\frac{L_2}{2}\\ P_4 &... & 0 & 0 & 0 & 1 & 0 & \frac{1}{2} & &L_3'=\frac{L_3}{2}
  • #1
evinda
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If we have a linear programming problem that is of the form as the following:

$$\max (- x_1+ 2 x_2-3x_3) \\ x_1- \frac{1}{2} x_2+x_3+x_{4}=11 \\ 2x_2-x_3+x_5=0 \\ 2x_4+x_6=8 \\ x_i \geq 0, i \in \{ 1, \dots, 6 \}$$

we cannot use the simplex method since we cannot find a basic feasible non-degenerate solution , right?
 
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  • #2
Re: Optimal solution

evinda said:
If we have a linear programming problem that is of the form as the following:

$$\max (- x_1+ 2 x_2-3x_3) \\ x_1- \frac{1}{2} x_2+x_3+x_{4}=11 \\ 2x_2-x_3+x_5=0 \\ 2x_4x_6=8 \\ x_i \geq 0, i \in \{ 1, \dots, 6 \}$$

we cannot use the simplex method since we cannot find a basic feasible non-degenerate solution , right?

Hey evinda! (Smile)

I think we can still use the simplex method.
A degenerate basic feasible solution does not prohibit that - it's just something to be careful with. (Nerd)
 
  • #3
Re: Optimal solution

I like Serena said:
Hey evinda! (Smile)

I think we can still use the simplex method.
A degenerate basic feasible solution does not prohibit that - it's just something to be careful with. (Nerd)

So we pick $(11,0,0,0,0,8)$ as the initial solution? (Thinking)

- - - Updated - - -

But then don't we have just two basic variables? Or am I wrong? (Thinking)
 
  • #4
Re: Optimal solution

evinda said:
So we pick $(11,0,0,0,0,8)$ as the initial solution? (Thinking)

But then don't we have just two basic variables? Or am I wrong? (Thinking)

I think that's not a solution. (Shake)

Can you make an initial tableau? (Wondering)
 
  • #5
Re: Optimal solution

I like Serena said:
I think that's not a solution. (Shake)

Can you make an initial tableau? (Wondering)

$\begin{bmatrix}
B & b & P_1 & P_2 & P_3 & P_4 & P_5 & P_6 & \theta\\
P_1 & 11 & 1 & -\frac{1}{2} & 1 & 1 & 0 & 0 & \\
P_5 & 0 & 0 & 2 & -1 & 0 & 1 & 0 & \\
P_6 & 8 & 0 & 0 & 0 & 2 & 0 & 1 & \\
& z & 1 & -2 & 3 & 0 & 0 &0 &
\end{bmatrix}$

Right?
 
  • #6
Is there a typo in the 3rd equation? (Wondering)
 
  • #7
I like Serena said:
Is there a typo in the 3rd equation? (Wondering)

Oh yes, I am sorry...
It should be $2x_4+x_6=8$... (Blush)
 
  • #8
Re: Optimal solution

evinda said:
So we pick $(11,0,0,0,0,8)$ as the initial solution? (Thinking)

But then don't we have just two basic variables? Or am I wrong? (Thinking)

Then that initial solution is fine.
And we will still have 3 basic variables.
They correspond to the columns with a single non-zero entry. (Mmm)
 
  • #9
Re: Optimal solution

I like Serena said:
Then that initial solution is fine.
And we will still have 3 basic variables.
They correspond to the columns with a single non-zero entry. (Mmm)
Then we get this:

$\begin{matrix}
B & b & P_1 & P_2 & P_3 & P_4 & P_5 & P_6 & \theta & \\
P_1 & 11 & 1 & 0 & \frac{3}{4} & 1 & \frac{1}{4} & 0 & &L_1'=L_1+ \frac{1}{2}L_2' \\
P_2 & 0 & 0 & 1 & -\frac{1}{2} & 0 & \frac{1}{2} & 0 & & L_2'=\frac{L_2}{2}\\
P_6 & 8 & 0 & 0 & 0 & 2 & 0 & 1 & &L_3'=L_3 \\
& z & 1 & 0 & 2 & 0 & 1 &0 & & L_4'=L_4+2L_2'
\end{matrix}$

Do we accept this tableau, although it gives again a degenerate basic feasible solution? (Thinking)

If so, then it gives the optimal solution, right?
 
  • #10
Re: Optimal solution

evinda said:
Do we accept this tableau, although it gives again a degenerate basic feasible solution? (Thinking)

If so, then it gives the optimal solution, right?

That's the problem with a degenerate condition - we can't be sure yet.
So there may still be a better solution.
We have to keep trying. (Thinking)
 
  • #11
Re: Optimal solution

I like Serena said:
That's the problem with a degenerate condition - we can't be sure yet.
So there may still be a better solution.
We have to keep trying. (Thinking)

So we apply the simplex method till what criterion is satisfied? (Thinking)
 
  • #12
Re: Optimal solution

evinda said:
So we apply the simplex method till what criterion is satisfied? (Thinking)

Until it's not degenerate and it's optimal, or until we cannot find a more optimal solution. (Nerd)
 
  • #13
Re: Optimal solution

I like Serena said:
Until it's not degenerate and it's optimal, or until we cannot find a more optimal solution. (Nerd)

A ok... In this case, do we choose any of $P_3, P_4,P_5$ to get in the basis or do we take into consideration an other criterion? (Thinking)
 
  • #14
Re: Optimal solution

evinda said:
A ok... In this case, do we choose any of $P_3, P_4,P_5$ to get in the basis or do we take into consideration an other criterion? (Thinking)

Which one will get us out of the degenerate condition? (Wondering)
 
  • #15
Re: Optimal solution

I like Serena said:
Which one will get us out of the degenerate condition? (Wondering)

Both $P_3$ and $P_5$, right? (Thinking)

I chose $P_3$ and I got the following tableau:$\begin{matrix}
B & b & P_1 & P_2 & P_3 & P_4 & P_5 & P_6 & & \theta\\
P_3 & \frac{44}{3} & \frac{4}{3} & 0 & 1 & \frac{4}{3} & \frac{1}{3} & 0 & 11 &L_1''=\frac{L_1' 4}{3} \\
P_2 & \frac{22}{3} & \frac{2}{3} & 1 & 0 & \frac{2}{3} & \frac{2}{3} & 0 & 11 & L_2''=L_2'+\frac{1}{2}L_1''\\
P_6 & 8 & 0 & 0 & 0 & 2 & 0 & 1 & 4 &L_3''=L_3' \\
&z & -\frac{5}{3} & 0 & 0 & -\frac{8}{3} & \frac{1}{3} & 0 & & L_4''=L_4'-2L_1''
\end{matrix}$

$-\frac{5}{3}>-\frac{8}{3}$, thus $P_4$ gets in the basis and $P_6$ gets out of the basis.
Then I got the following tableau:

$\begin{matrix}
B & b & P_1 & P_2 & P_3 & P_4 & P_5 & P_6 & & \theta\\
P_3 & \frac{28}{3} & \frac{4}{3} & 0 & 1 & 0 & \frac{1}{3} & -\frac{2}{4} & \frac{28}{4} &L_1'''=L_1''-\frac{4}{3}L_3'' \\
P_2 & \frac{14}{3} & 0 & 1 & 0 & 0 & \frac{2}{3} & -\frac{1}{3} & - & L_2'''=L_2''-\frac{2}{3}L_3'''\\
P_4 & 4 & 0 & 0 & 0 & 1 & 0 & \frac{1}{2} & - &L_3'''=\frac{L_3''}{2} \\
&z & -\frac{5}{3} & 0 & 0 & 0 & \frac{1}{3} & \frac{4}{3} & & L_4'''=L_4''+\frac{8}{3}L_3'''
\end{matrix}$

Then $P_1$ gets in the basis and $P_3$ gets out of the basis:

$\begin{matrix}
B & b & P_1 & P_2 & P_3 & P_4 & P_5 & P_6 & & \theta\\
P_1 & \frac{28}{4} & 1 & 0 & \frac{3}{4} & 0 & \frac{1}{4} & -\frac{1}{2} & &L_1''''=\frac{L_1''' 3}{4} \\
P_2 & \frac{14}{3} & 0 & 1 & 0 & 0 & \frac{2}{3} & -\frac{1}{3} & & L_2''''=L_2'''\\
P_4 & 4 & 0 & 0 & 0 & 1 & 0 & \frac{1}{2} & - &L_3''''=L_3''' \\
&z & 0 & 0 & \frac{5}{4} & 0 & \frac{3}{4} & \frac{3}{4} & & L_4''''=L_4'''+\frac{5}{3}L_1''''
\end{matrix}$

Is everything right? (Thinking)

If so, do we deduce now from the fact that $z_k''''-c_k \geq 0 \forall k$ and that we have a non-degenerate basic feasible solution, that it is the optimal one? (Thinking)
 
  • #16
Re: Optimal solution

We had the initial tableau:
evinda said:
$\begin{bmatrix}
B & b & P_1 & P_2 & P_3 & P_4 & P_5 & P_6 & \theta\\
P_1 & 11 & 1 & -\frac{1}{2} & 1 & 1 & 0 & 0 & \\
P_5 & 0 & 0 & 2 & -1 & 0 & 1 & 0 & \\
P_6 & 8 & 0 & 0 & 0 & 2 & 0 & 1 & \\
& z & 1 & -2 & 3 & 0 & 0 &0 &
\end{bmatrix}$

Then we picked the initial solution $(11,0,0,0,0,8)$ and got this:
evinda said:
Then we get this:
$\begin{matrix}
B & b & P_1 & P_2 & P_3 & P_4 & P_5 & P_6 & \theta & \\
P_1 & 11 & 1 & 0 & \frac{3}{4} & 1 & \frac{1}{4} & 0 & &L_1'=L_1+ \frac{1}{2}L_2' \\
P_2 & 0 & 0 & 1 & -\frac{1}{2} & 0 & \frac{1}{2} & 0 & & L_2'=\frac{L_2}{2}\\
P_6 & 8 & 0 & 0 & 0 & 2 & 0 & 1 & &L_3'=L_3 \\
& z & 1 & 0 & 2 & 0 & 1 &0 & & L_4'=L_4+2L_2'
\end{matrix}$

evinda said:
Is everything right? (Thinking)

I think there is a mistake in that tableau. (Worried)

Shouldn't it be:
\begin{array}{cc|cccccc}
B & b & P_1 & P_2 & P_3 & P_4 & P_5 & P_6 \\
\hline
P_1 & 11 & 1 & & \frac{1}{2} & 1 & \frac{1}{2} & \\
P_2 & 0 & & 1 & -\frac{1}{2} & & \frac{1}{2} & \\
P_6 & 8 & & & & 2 & & 1 \\
\hline
& & 1 & & 2 & & 1 &
\end{array}
(Wondering)
 
  • #17
Re: Optimal solution

I like Serena said:
We had the initial tableau:Then we picked the initial solution $(11,0,0,0,0,8)$ and got this:

I think there is a mistake in that tableau. (Worried)

Shouldn't it be:
\begin{array}{cc|cccccc}
B & b & P_1 & P_2 & P_3 & P_4 & P_5 & P_6 \\
\hline
P_1 & 11 & 1 & & \frac{1}{2} & 1 & \frac{1}{2} & \\
P_2 & 0 & & 1 & -\frac{1}{2} & & \frac{1}{2} & \\
P_6 & 8 & & & & 2 & & 1 \\
\hline
& & 1 & & 2 & & 1 &
\end{array}
(Wondering)

I retried it and I got again the same result... (Worried)

Isn't it $L_1'=L_1+ \frac{1}{2} L_2'$ ?

At the first row and third column we have the number $1$.
And then $1+ \frac{1}{2} \left( - \frac{1}{2} \right)=1- \frac{1}{4}=\frac{4-1}{4}=\frac{3}{4}$

Or am I wrong? (Thinking)
 
  • #18
If so, then the optimal solution is $\frac{7}{3}$, right? (Thinking)
 
  • #19
The optimal solution has an objective value of $-7$.
Currently you're at $-11$.
To get there, we need $P_4$ in the basis.
 
  • #20
I like Serena said:
The optimal solution has an objective value of $-7$.
Currently you're at $-11$.
To get there, we need $P_4$ in the basis.

How did you find that the optimal solution has an objective value of $-7$? (Thinking)

There should be a mistake at one of my tableaus. But I always find the same ones... (Sweating)
Do you have an idea what might be wrong?
 
  • #21
Let's start from the beginning. (Sweating)
We have the initial tableau:
\begin{array}{cc|ccccc}
B &b &P1 &P2 &P3 &P4 &P5 &P6 \\
\hline
P1 &11 &1 &-0.5 &1 &1 & & \\
P5 &0 & &\enclose{circle}{2} &-1 & &1 & \\
P6 &8 & & & &2 & &1 \\
\hline
& &1 &-2 &3 & & & \\
\end{array}
With corresponding solution $(11, 0, 0, 0, 0, 8)$ and objective value $z=-x_1+2x_2-3x_3=-11$.

After selecting the circled $\enclose{circle}2$ we get:
\begin{array}{cc|ccccc}
B &b &P1 &P2 &P3 &P4 &P5 &P6 \\
\hline
P1 &11 &1 &0 &0.75 &1 &0.25 &0 \\
P2 &0 &0 &1 &\enclose{circle}{-0.5} &0 &0.5 &0 \\
P6 &8 &0 &0 &0 &2 &0 &1 \\
\hline
&0 &1 &0 &2 &0 &1 &0 \\
\end{array}
With corresponding solution $(11, 0, 0, 0, 0, 8)$ and objective value $z=-11$.
I think you also had this. (Thinking)

I believe you then selected $P_3$, in which case I'm getting:
\begin{array}{cc|ccccc}
B &b &P1 &P2 &P3 &P4 &P5 &P6 \\
\hline
P1 &11 &1 &1.5 &0 &1 &1 &0 \\
P3 &0 &0 &-2 &1 &0 &-1 &0 \\
P6 &8 &0 &0 &0 &2 &0 &1 \\
\hline
&0 &1 &4 &0 &0 &3 &0 \\
\end{array}
But this looks different from what you have... :confused:
 
  • #22
I like Serena said:
Let's start from the beginning. (Sweating)
We have the initial tableau:
\begin{array}{cc|ccccc}
B &b &P1 &P2 &P3 &P4 &P5 &P6 \\
\hline
P1 &11 &1 &-0.5 &1 &1 & & \\
P5 &0 & &\enclose{circle}{2} &-1 & &1 & \\
P6 &8 & & & &2 & &1 \\
\hline
& &1 &-2 &3 & & & \\
\end{array}
With corresponding solution $(11, 0, 0, 0, 0, 8)$ and objective value $z=-x_1+2x_2-3x_3=-11$.

After selecting the circled $\enclose{circle}2$ we get:
\begin{array}{cc|ccccc}
B &b &P1 &P2 &P3 &P4 &P5 &P6 \\
\hline
P1 &11 &1 &0 &0.75 &1 &0.25 &0 \\
P2 &0 &0 &1 &\enclose{circle}{-0.5} &0 &0.5 &0 \\
P6 &8 &0 &0 &0 &2 &0 &1 \\
\hline
&0 &1 &0 &2 &0 &1 &0 \\
\end{array}
With corresponding solution $(11, 0, 0, 0, 0, 8)$ and objective value $z=-11$.
I think you also had this. (Thinking)

I believe you then selected $P_3$, in which case I'm getting:
\begin{array}{cc|ccccc}
B &b &P1 &P2 &P3 &P4 &P5 &P6 \\
\hline
P1 &11 &1 &1.5 &0 &1 &1 &0 \\
P3 &0 &0 &-2 &1 &0 &-1 &0 \\
P6 &8 &0 &0 &0 &2 &0 &1 \\
\hline
&0 &1 &4 &0 &0 &3 &0 \\
\end{array}
But this looks different from what you have... :confused:
Before we put $P_3$ in the basis we see that the pivot is $\frac{3}{4}$, so we have to multiply the first line by $\frac{4}{3}$, don't we? (Thinking)
 
  • #23
evinda said:
Before we put $P_3$ in the basis we see that the pivot is $\frac{3}{4}$, so we have to multiply the first line by $\frac{4}{3}$, don't we? (Thinking)

I picked the pivot $\enclose{circle}{-\frac 12}$. Doesn't that one have a lower $\theta$ value? (Wondering)
 
  • #24
I like Serena said:
I picked the pivot $\enclose{circle}{-\frac 12}$. Doesn't that one have a lower $\theta$ value? (Wondering)

I didn't pick it since $\theta$ is defined as follows:

$$\theta= \min_i \left \{ \frac{x_{i0}}{x_{ij}}: x_{ij}>0\right \}>0$$

(Thinking)
 
  • #25
evinda said:
I didn't pick it since $\theta$ is defined as follows:

$$\theta= \min_i \left \{ \frac{x_{i0}}{x_{ij}}: x_{ij}>0\right \}>0$$

(Thinking)

Simplex algorithms vary. What is your algorithm exactly?
Which column should we select?
And does it take degenerate tableaux into account? (Wondering)
 
  • #26
$(\overline{x_0})$ is a basic non-degenerate feasible solution

Step 1: We create a $(m+1) \times (n+4)$ matrix as follows:

  • At the first column we write the basic columns $P_1, \dots, P_m$
  • At the second column we write the values of the corresponding cost factor.
  • At the third column we write the initial basic non-degenerate feasible solution $\overline{x_0}$.
  • At the next n columns we write the elements of the columns of the matrix $A$.
  • The last column remains currently empty.
  • At the last row we write the value $z_0$ of the objective function that corresponds to the solution $\overline{x_0}$, and also the values of the differences $z_k-c_k, k=1, \dots, n$.
Step 2: We check if $\overline{x_0}$ is optimal by checking the differences $z_k-c_k, k=m+1, \dots, n$.

  • If $z_k-c_k \geq 0 \forall k=m+1, \dots, n$ then $\overline{x_0}$ is an optimal solution.
  • If $z_j-c_j<0$ for some $j \in \{ m+1, \dots, n \}$ then $\overline{x_0}$ is not an optimal solution.
Step 3: How do I choose the new column $P_j$ that gets into the basis ( of $\mathbb{R}^m$)

The column that will get basic is given by the following relation:

$P_j$ such that $|z_j-c_j|= \max_k \{ |z_k-c_k|: z_k-c_k<0\}$

Step 4: How do I choose the column $P_i$ that gets out of the initial basis $B=P_1, \dots, P_m)$

$P_i$ such that $\frac{x_{i0}}{x_{ij}}= \min \{ \frac{x_{k0}}{x_{kj}}: x_{kj}>0\}$Step 5: We compute thecoefficients of the next tableau from the relations:

$$x_{ik}'=\frac{x_{ik}}{x_{ij}} , k=0,1, \dots, n \\ x_{sk}'=x_{sk}-\frac{x_{ik}}{x_{ij}} x_{sj}, s=1,2, \dots, m, m+1, s \neq i, k=0,1,2, \dots, n \\ x_{(m+1)k}=z_k-c_k, k=1, \dots, n \\ x_{(m+1)0}=z_0$$

$$\Gamma_i'=\frac{1}{x_{ij}} \Gamma_i \\ \Gamma_m'=\Gamma_m- x_{mj} \Gamma_i'$$
 
  • #27
Indeed. It does not take a degenerate tableau into account.
It considers a situation where $z_k−c_k=0$ as an optimal solution.
But that is not necessarily the case when one of the $b$ values is $0$.
In such a case we need an extension to the algorithm to find the actual optimal solution.

Does your course material mention what to do when we have a degenerate basic feasible solution? (Wondering)
 
  • #28
I found this now in my textbook:

Degenerate solutions:

  • Obviously if $\theta_0=\min_i \left\{ \frac{x_{i0}}{x_{ij}}: x_{ij}>0\right\}$ is achieved in more than one rows ( for example $\theta_0=\frac{x_{10}}{x_{1j}}=\frac{x_{20}}{x_{2j}}$), then the corresponding solution $x_1$ is degenerate.
  • If the initial solution is degenerate , then we might have had $x_{10}=0, x_{1j}>0$, thus $\theta_0=0$ and therefore $x_1=x_0$ and $z_1=z_0$, i.e. that the solution couldn't be improved.At both of the above cases, we turn the degenerate solution to non-degenerate, replacing $0$ of the basic variable by $\epsilon>0$, arbitrarily small and we continue normally till we find the optimal solution, and then we set again $\epsilon=0$.
If we do this, will we get a different tableau? (Thinking)
 
  • #29
The last tableau that we get is the following, right?

$\begin{matrix}
B & c_B & b & P_1 & P_2 & P_3 & P_4 & P_5 & P_6 & \theta & \\
P_1 & -1& 7 & 1 & 0 & \frac{3}{4} & 0 & \frac{1}{4} & -\frac{1}{2} & & L_1''''=L_1''' \frac{3}{4}\\
P_2 & 2 & 0 & 0 & 1 & -\frac{1}{2} & 0 & \frac{1}{2} & 0 & & L_2''''=L_2'''-\frac{2}{3}L_1''''\\
P_4 & 0 & 4 & 0 & 0 & 0 &1 & 0 & \frac{1}{2} & & L_3''''=L_3'''\\
& z & -7 & 0 & 0 & \frac{5}{4} & 0 & \frac{3}{4} & \frac{1}{2} & & L_4''''=L_4'''+\frac{5}{3}L_1''''
\end{matrix}$If we replace $0$ of the basic variable by $\epsilon$ and then set $\epsilon=0$ at the last tableau to find the solution, don't we get the same tableau? (Thinking)
 

1. What are the limitations of the Simplex Method for solving linear programming problems?

The Simplex Method is limited to solving problems with linear constraints and a linear objective function. It also requires that all variables have non-negative coefficients and that the problem is in standard form. Additionally, it may not always find the optimal solution if there are multiple optimal solutions or if the problem is unbounded.

2. Can the Simplex Method be used for non-linear programming problems?

No, the Simplex Method is only applicable to linear programming problems. Non-linear programming problems require different techniques, such as the Gradient Descent Method.

3. What are some exceptions where the Simplex Method may not be the most efficient method for solving linear programming problems?

The Simplex Method may not be the most efficient method for solving problems with a large number of variables or constraints. In these cases, other methods such as the Interior Point Method may be more efficient.

4. How does the initial basic feasible solution affect the performance of the Simplex Method?

The Simplex Method relies on an initial basic feasible solution to start the iteration process. If the initial solution is far from the optimal solution, the method may take longer to converge. Therefore, choosing a good initial solution can improve the efficiency of the Simplex Method.

5. Are there any real-world applications where the Simplex Method may not be suitable?

The Simplex Method may not be suitable for problems with integer or binary constraints, such as in integer programming or binary optimization problems. In these cases, specialized methods such as the Branch and Bound Method may be more effective.

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