Solve Linear Programming Graphically: 2 Train-Lines at Central Station

In summary, two train-lines leave the same central station at the same time, one with 2 departures per hour and the other with 1 departure per hour. There is a total of 100 trains and each train can hold 150 passengers. In order for the trains to meet the demand, the number of people that can ride the trains must be larger than the demand. Therefore, x + y \leq 100. To plot this graphically, x and y must also satisfy x \leq 24 and y \leq 20. This can be plotted as plot 24, 20.
  • #1
Dr-NiKoN
94
0
2 train-lines leave the same central station at the same time.
line 1: [itex]f(x) = 6000 + 50x[/itex]
line 2: [itex]g(y) = 2000 + 50y[/itex]

x and y are the number of departures pr. hour. line 1 can have 2 departures pr. hour pr. trian, and line 2 can only have 1 departure pr. hour pr. train.
There is a total of 100 trains.

I'm supposed to show this graphically.

I have:
[itex]x + y \geq 100[/itex]
Since line 1 can have 2 departures pr. hour. pr. train, I also have:
[itex]f(x) = 6000 + 50(2)x[/itex]

But, I'm confused on how I show this graphically? What do I need to plot here?

Plotting f(x) and g(y) doesn't make any sense at all.
 
Last edited:
Physics news on Phys.org
  • #2
Are you sure you don't want [tex]x+y \leq 100[/tex]?

Are you sure that the equations are really what you represent them as in general - It seems like [tex]f(x)[/tex] and [tex]g(y)[/tex] might be the number of people each train handles, with [tex]x[/tex] and [tex]y[/tex] the number of departues of that type of train.

So, let's say that [tex]t_1[/tex] and [tex]t_2[/tex] are the numbers of each type of train. Then you have:
[tex]t_1+t_2 \leq 100 [/tex] - The number of trains is limited
[tex]t_1\geq 0[/tex] - It's impossibe to have fewer than 0 trains
[tex]t_2\geq 0[/tex]
The feasible region should be a triangle, with two sides along the axes.

And I'll guess that you're going to maximize
[tex]p=f(x)+g(y)=6000+50 t_1 + 2000 + 2 (50) t_2=8000+50t_1+100t_2[/tex]
 
  • #3
Ah, that helps. I'll see what I come up with this.

thanks a lot :)
 
  • #4
Hm, I misunderstood.

Each train can hold 150 passagers. You need to show graphically which combinations of x and y that can handle all the passengers that wants to take the train.
The amount of passengers that wants to take the train are given by f(x) and g(x).

So, this amounts to:

[itex]f(x) = \frac{6000 + 100x}{150}[/itex] (There are 2 departures for each departure in g(x).)

[itex]g(x) = \frac{2000 + 50x}{150}[/itex]

Wouldn't this be correct? I'm not sure how the unequalities would look like though.
[itex] x + y \leq 100[/itex]

[itex]40 + \frac{1}{1.5}x \geq ?[/itex]

[itex]\frac{20}{1.5} + \frac{10}{3}x \geq ?[/itex]
 
Last edited:
  • #5
I'm sorry, but I can't really follow your last post.

Let's say, for a moment that the number of people that want to ride train [tex]t_x[/tex] is
[tex]f(x)=6000+100x[/tex] where [tex]x[/tex] is the number of trains, then, in order for the trains to meet the demand the number of people that can ride the trains must be larger than the demand:
[tex]2 \times 150 \times x[/tex]
is the number of people that train route [tex]t_x[/tex] can handle per hour based on two departures per train per hour. An that must be larger than the number of people that want to ride trains on that route so
[tex] 2\times 150 \times x \geq f(x)=6000+100x[/tex]
[tex]300 \times x \geq 6000 + 100x [/tex]
[tex]x \geq 30[/tex]

The inital stuff might not be set up right, so you'll have to check it out. You'll do a similar thing for y, and then the [tex]x+y \leq 100[/tex] condition.
 
  • #6
Ah, yes, this makes sense. Thanks :)

Now I've stumbled upon another problem, which probably isn't to related to this forum. I'll ask anyway.
How do I plot this with gnuplot?
I have:
[itex]x + y \leq 100[/itex]
[itex]x \leq 24[/itex]
[itex]y \leq 20[/itex]

I can plot the first and the last with:
plot 100 - x, 20

But, how do i plot x = 24?
 

1. What is linear programming?

Linear programming is a mathematical method used to find the optimal solution for a problem with linear constraints. It involves maximizing or minimizing a linear objective function while satisfying a set of linear constraints.

2. How is linear programming used in the context of 2 train-lines at Central Station?

In the context of 2 train-lines at Central Station, linear programming can be used to optimize the train schedules and determine the most efficient use of resources, such as trains and platforms, while considering factors such as passenger demand and time constraints.

3. Can linear programming be solved graphically?

Yes, linear programming can be solved graphically by plotting the constraints and objective function on a graph and finding the point of intersection that maximizes or minimizes the objective function within the feasible region.

4. What are the advantages of solving linear programming graphically?

Solving linear programming graphically allows for a visual representation of the problem, making it easier to understand and interpret the results. It also does not require complex mathematical calculations, making it more accessible for those without a strong mathematical background.

5. Are there any limitations to solving linear programming graphically?

Yes, solving linear programming graphically is limited to problems with only two decision variables and a small number of constraints. It also relies on the accuracy of the graph and may not provide an exact solution, but rather an approximation.

Similar threads

  • Set Theory, Logic, Probability, Statistics
Replies
4
Views
859
  • Introductory Physics Homework Help
Replies
15
Views
1K
  • Introductory Physics Homework Help
Replies
6
Views
563
  • Calculus and Beyond Homework Help
Replies
1
Views
252
Replies
17
Views
2K
  • Set Theory, Logic, Probability, Statistics
Replies
9
Views
2K
  • Special and General Relativity
Replies
25
Views
845
  • Calculus and Beyond Homework Help
Replies
8
Views
449
  • Introductory Physics Homework Help
Replies
5
Views
2K
  • Introductory Physics Homework Help
Replies
14
Views
2K
Back
Top