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The tableau below shows the optimal solution for Ile problem MAxizt 2, sulypect o 2 54(CI)(C21Row Basic Basic Number Index VarableRight SideX 3Reoptimize after the ...

Question

The tableau below shows the optimal solution for Ile problem MAxizt 2, sulypect o 2 54(CI)(C21Row Basic Basic Number Index VarableRight SideX 3Reoptimize after the original problem is changed so the right-hand side f (CI) is and the right-hand side of (C2) is Reoptimize alter the original problem is changed s0 the objective coefficient of x; and the objective coellicient of X1 iS Reoptimize Using the dual simplex method after adding the constraint x} is less than to the origmnal problem

The tableau below shows the optimal solution for Ile problem MAxizt 2, sulypect o 2 54 (CI) (C21 Row Basic Basic Number Index Varable Right Side X 3 Reoptimize after the original problem is changed so the right-hand side f (CI) is and the right-hand side of (C2) is Reoptimize alter the original problem is changed s0 the objective coefficient of x; and the objective coellicient of X1 iS Reoptimize Using the dual simplex method after adding the constraint x} is less than to the origmnal problem



Answers

Introduce slack variables as necessary, then write the initial simplex tableau for each linear programming problem.
Find $x_{1} \geq 0$ and $x_{2} \geq 0$ such that
$$
\begin{aligned} 3 x_{1}+x_{2} & \leq 12 \\ x_{1}+x_{2} & \leq 15 \end{aligned}
$$
and $z=2 x_{1}+x_{2}$ is maximized.

Get of this question. They have a game station problem for which they want the, uh, slack wearable. Let's see, to constrain self reliance and to slack variable so we can write them as equality. We use our first look agreeable for this country. 100 second, like variable trends and joining that manipulate our objective function that we want a next life. One minus is equal toe. And now they want us to write the initial look. Thanks. One there. Uh, zero. Where is the only that major cities for our other Illini. Some problems. Fine. For 010 200 was in the car. Those of the right hand side were all very well. And now yeah, one. There are one zero. Why not only an initial.

For this problem big either. Uh uh. When you're inequality. Very maximization from. And they wanted the ads like variables. The Tournament of polity. Older two, primary constraints. I've added black variable love one. That's when you first came straight here. That equals that will use their second in a strange can in quality. All right, call it in the last name. What are the function? Bringing variables. One along in So you can transcribe are blue. Maya? Yeah, right in the Yeah. Now let's start. All right. Coefficients were variables. 11100 Right hand side. I'm strange for green 010 48. They are objective. Negative one.

This time they want us are slack. Variable on right the image Blix Temblor Be that three of two primary country track variable like where? No. And now. All right, train quality first, like variable strength, but for and we have our objective function one. Make it minus of the and brought them over to the same side of an equation because it makes it simpler, right? Our initial simplex. Well, it's a risk constraint. It's now inequality. For one. There's no coefficient for American shape with this one too. 01 one Very hands on the object and get one zero. We forgot Hersey calm. And then on the right hand side, we have a zero now. This is our initial.

They want do as slack wearables to our maximization problems. We have three primary constraint. You are gonna need black variable one. Okay, turn those strings. Inequality first. Like wearable there. Five. What? Right. Three And Leslie, let your arrange our objective. Timex bringing variable living My mystery, my see 20 Okay, So let, uh, greater in the shore. Look for this problem. 11 taking their coefficients one like we would. Another terms of linear equation problem. Probably variable. Okay, that's constraint. One zero zero. No, this is the S to injury. Coefficient is one one. I have no history and no zero growth. All right, third constraint. One 00 It does have an estate has nothing. And then we also put armed one. Vera, this is on initial simplex tableau for this probe.


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