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According to the Fundamental Theorem of linear programming, if either a linear program or its dual has no feasible point, then the other one has no solution. Illustrate this assertion with an example.

Short Answer

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We constructed a linear program (LP) and its dual linear program (DLP). After analyzing the LP, we found it has no feasible region, as no point satisfies all three constraints simultaneously. According to the Fundamental Theorem of linear programming, if the LP has no feasible point, then its DLP must have no solution. True to the theorem, we found that there is no combination for y_1, y_2, and y_3 that satisfy all DLP constraints simultaneously, proving the assertion.

Step by step solution

01

Create a linear program

: Let's create a linear program (LP). Maximize: \(z = 2x_1 + 3x_2\) Subject to: \(x_1 + x_2 ≤ 1\) \(x_1 - x_2 ≥ 3\) \(-2x_1 + 3x_2 ≤ 1\) \(x_1, x_2 \geq 0\)
02

Create the dual of the linear program

: Now, let's construct the dual linear program (DLP) for the given LP. Minimize: \(w = y_1 + 3y_2 + y_3\) Subject to: \(y_1 + y_2 - 2y_3 ≥ 2\) \(y_1 - y_3 + 3y_3 ≥ 3\) \(y_1, y_2, y_3\geq 0\)
03

Check for feasible region in the linear program

: Now, let's check whether the given LP has a feasible region (in which an optimal solution could exist) by finding the intersection of the constraints. Plot the constraints: \(x_1 + x_2 = 1\), \(x_1 - x_2 = 3\), and \(-2x_1 + 3x_2 = 1\). Upon analyzing the plots, we can see that no point satisfies all three constraints simultaneously, indicating that the LP does not have a feasible region.
04

Check the dual linear program for a solution

: According to the Fundamental Theorem of linear programming, since the given LP has no feasible point, its DLP should have no solution: Check the DLP constraints: \(y_1 + y_2 - 2y_3 = 2\), \(y_1 - y_3 + 3y_3 =3\), and \(y_1, y_2, y_3\geq 0\). Upon attempting to solve the DLP constraints, we find that there is no combination of values for y_1, y_2, and y_3 that satisfy all constraints simultaneously. Therefore, the DLP does not have a solution. Thus, the given example illustrates the Fundamental Theorem of linear programming asserting that if either a linear program or its dual has no feasible point, the other one also has no solution.

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Most popular questions from this chapter

Minimize \(\quad \mathrm{x}_{1}+\mathrm{x}_{2}\) Subject to: \(\begin{aligned} & \mathrm{x}_{1}+2 \mathrm{x}_{2} \leq 4 \\ & \mathrm{x}_{2} \leq 1 \\ & \mathrm{x}_{1}, \mathrm{x}_{2} \geq 0 \end{aligned}\) Find a basic feasible solution to the above problem, starting from a b.f.s with xi and in the basis.

Graph the system \(\mathrm{x} \geq 4\) and \(2 x \leq 18\)

The Brown Company has two warehouses and three retail outlets. Warehouse number one (which will be denoted by \(\mathrm{W}_{1}\) ) has a capacity of 12 units; warehouse number two \(\left(\mathrm{W}_{2}\right)\) holds 8 units. These warehouses must ship the product to the three outlets, denoted by \(\mathrm{O}_{1}, \mathrm{O}_{2}\), and \(\mathrm{O}_{3} \cdot \mathrm{O}_{1}\) requires 8 units. \(\mathrm{O}_{2}\) requires 7 units, and \(\mathrm{O}_{3}\) requires 5 units. Thus, there is a total storage capacity of 20 units, and also a demand for 20 units. The question is, which warehouse should ship how many units to which outlet? (The objective being, of course, to accomplish this at the least possible cost.) Costs of shipping from either warehouse to any of the outlets are known and are summarized in the following table, which also sets forth the warehouse capacities and the needs of the retail outlets: $$ \begin{array}{|c|c|c|c|c|} \hline & \mathrm{O}_{1} & \mathrm{O}_{2} & \mathrm{O}_{3} & \text { Capacity } \\\ \hline \mathrm{W}_{1} \ldots \ldots \ldots \ldots . . & \$ 3.00 & \$ 5.00 & \$ 3.00 & 12 \\ \hline \mathrm{W}_{2} \ldots \ldots \ldots \ldots . . & 2.00 & 7.00 & 1.00 & 8 \\\ \hline \text { Needs (units) } & 8 & 7 & 5 & \\ \hline \end{array} $$

Consider the following problem: \(\begin{aligned}&\text { Minimize } & z=2 x_{1}+4 x_{2} \\\&\text { subject to } & x_{1}+5 x_{2} \leq 80 \\\& & 4 x_{1}+2 x_{2} \geq 20 \\\& & x_{1}+x_{2}=10 \\\& & x_{1}, x_{2} \geq 0\end{aligned}\) Find the canonical form.

Suppose that we have 2 factories and 3 warehouses. Factory I makes 40 widgets. Factory II makes 50 widgets. Warehouse A stores 15 widgets. Warehouse B stores 45 widgets. Warehouse C stores 30 widgets. It costs \(\$ 80\) to ship one widget from Factory I to warehouse A, \(\$ 75\) to ship one widget from Factory \(\mathrm{I}\) to warehouse \(\mathrm{B}, \$ 60\) to ship one widget from Factory I to warehouse C, \(\$ 65\) per widget to ship from Factory II to warehouse A, \(\$ 70\) per widget to ship from Factory II to warehouse \(\mathrm{B}\), and \(\$ 75\) per widget to ship from Factory II to warehouse \(\mathrm{C}\). 1) Set up the linear programming problem to find the shipping pattern which minimizes the total cost. 2) Find a feasible (but not necessarily optimal) solution to the problem of finding a shipping pattern using the Northwest Corner Algorithm. 3) Use the Minimum Cell Method to find a feasible solution to the shipping problem.

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