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Linear Programming: Introduction (page 1 of 5)
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Sections: Optimizing linear systems, Setting up word problems
Linear programming is the process of taking various linear inequalities relating to some situation, and finding the 'best' value obtainable under those conditions. A typical example would be taking the limitations of materials and labor, and then determining the 'best' production levels for maximal profits under those conditions.
In 'real life', linear programming is part of a very important area of mathematics called 'optimization techniques'. This field of study (or at least the applied results of it) are used every day in the organization and allocation of resources. These 'real life' systems can have dozens or hundreds of variables, or more. In algebra, though, you'll only work with the simple (and graphable) two-variable linear case.
The general process for solving linear-programming exercises is to graph the inequalities (called the 'constraints') to form a walled-off area on the x,y-plane (called the 'feasibility region'). Then you figure out the coordinates of the corners of this feasibility region (that is, you find the intersection points of the various pairs of lines), and test these corner points in the formula (called the 'optimization equation') for which you're trying to find the highest or lowest value.
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- Find the maximal and minimal value of z = 3x + 4y subject to the following constraints:
= 0, x - y <= 2'>
The three inequalities in the curly braces are the constraints. The area of the plane that they mark off will be the feasibility region. The formula 'z = 3x + 4y' is the optimization equation. I need to find the (x, y) corner points of the feasibility region that return the largest and smallest values of z.
My first step is to solve each inequality for the more-easily graphed equivalent forms:
It's easy to graph the system: Copyright © Elizabeth Stapel 2006-2011 All Rights Reserved
To find the corner points -- which aren't always clear from the graph -- I'll pair the lines (thus forming a system of linear equations) and solve:
y = –( 1/2 )x + 7 | y = –( 1/2 )x + 7 | y = 3x |
–( 1/2 )x + 7 = 3x y = 3(2) = 6 | –( 1/2 )x + 7 = x – 2 y = (6) – 2 = 4 | 3x = x – 2 y = 3(–1) = –3 |
corner point at (2, 6) | corner point at (6, 4) | corner pt. at (–1, –3) |
So the corner points are (2, 6), (6, 4), and (–1, –3).
Somebody really smart proved that, for linear systems like this, the maximum and minimum values of the optimization equation will always be on the corners of the feasibility region. So, to find the solution to this exercise, I only need to plug these three points into 'z = 3x + 4y'.
(2, 6): z = 3(2) + 4(6) = 6 + 24 = 30
(6, 4): z = 3(6) + 4(4) = 18 + 16 = 34
(–1, –3): z = 3(–1) + 4(–3) = –3 – 12 = –15
Then the maximum of z = 34 occurs at (6, 4),
and the minimum of z = –15 occurs at (–1, –3).
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Cite this article as: | Stapel, Elizabeth. 'Linear Programming: Introduction.' Purplemath. Available from |
Purplemath
The general technique for solving bigger-than-quadratic polynomials is pretty straightforward, but the process can be time-consuming.
Note: The terminology for this topic is often used carelessly. Technically, one 'solves' an equation, such as '(polynomal) equals (zero)'; one 'finds the roots' of a function, such as '(y) equals (polynomial)'. On this page, regardless of how the topic is framed, the point will be to find all of the solutions to '(polynomial) equals (zero)', even if the question is stated differently, such as 'Find the roots of (y) equals (polynomial)'.
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The first step in finding the solutions of (that is, the x-intercepts of, plus any complex-valued roots of) a given polynomial function is to apply the Rational Roots Test to the polynomial's leading coefficient and constant term, in order to get a list of values that might possibly be solutions to the related polynomial equation. Your hand-in work is probably expected to contain this list, so write this out neatly.
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You can follow this up with an application of Descartes' Rule of Signs, if you like, to narrow down which possible zeroes might be best to check. On the other hand, if you've got a graphing calculator you can use, it's easy to do a graph. The x-intercepts of the graph are the same as the (real-valued) zeroes of the equation. Seeing where the line looks as though it crosses the x-axis can quickly narrow down your list of possible zeroes that you'll want first to check.
Once you've found an x-value that you want to test, you then use synthetic division to see if you can get a zero remainder. If you do get a zero remainder, then you've not only found a zero of the original polynomial, but you've also reduced your polynomial by one degree, by effectively removing one factor.
Remember that synthetic division is, among other things, a form of polynomial division, so checking if x = a is a solution to '(polynomial) equals (zero)' is the same as dividing the linear factor x – a out of the related polynomial function '(y) equals (polynomial)'.
This also means that, after a successful division, you've also successfully taken a factor out. You should not then return to the original polynomial for your next computation for finding the other zeroes. You should instead work with the output of the synthetic division. It's smaller, so it's easier to work with.
(This method will be demonstrated in the examples below.)
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You should not be surprised to see some complicated solutions to your polynomials (that is, solutions containing square roots or complex numbers, or both); these zeroes will come from applying the Quadratic Formula to (what is usually) the final (quadratic) factor of your polynomial. You should expect that the answers will be messy.
Here's how the process plays out in practice:
Find all the zeroes of: y = 2x5 + 3x4 – 30x3 – 57x2 – 2x + 24
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First, I'll apply the Rational Roots Test—
Wait. Actually, the first thing I'll do is apply a trick I've learned. First, I'll check to see if either x = 1 or x = –1 is a root.
(These are the simplest roots to test for. This isn't an 'official' first step, but it can often be a timesaver, because (a) it's amazing how often one of these is a zero, and (b) you can just look at the powers and the numbers to figure out if either works, because of how 1 and –1 simplify.)
When x = 1, the polynomial evaluates as:
This isn't equal to zero, so x = 1 isn't a root. But when x = –1, I get:
–2 + 3 + 30 – 57 + 2 + 24 = 0
This time, it did equal zero, so now I know that x = –1 is a root, and I can take 'prove' this (in my hand-in work) by using synthetic division:
The last line of this division shows me with the new, smaller polynomial equation I'm working with now:
2x4 + x3 – 31x2 – 26x + 24 = 0
(I'd started with a degree-five polynomial. Gopanel 1 7 3 – manage web servers. Since I've effectively divided out the factor x + 1, I've reduced the degree of the polynomial by 1. That's how I know the last line of the division represents a degree-four polynomial.)
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I've taken care of checking the two easiest zeroes. Now I'll apply the Rational Roots Test to what's left in order to get a list of potential zeroes to try:
From experience (mostly by having worked extra homework problems), I've learned that most of these exercises have their zeroes somewhere near the middle of the list, rather than at the extremes. This isn't always true, of course, but it's usually better to stay away from the larger numbers, at least when I'm getting started.
The last line of this division shows me with the new, smaller polynomial equation I'm working with now:
2x4 + x3 – 31x2 – 26x + 24 = 0
(I'd started with a degree-five polynomial. Gopanel 1 7 3 – manage web servers. Since I've effectively divided out the factor x + 1, I've reduced the degree of the polynomial by 1. That's how I know the last line of the division represents a degree-four polynomial.)
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I've taken care of checking the two easiest zeroes. Now I'll apply the Rational Roots Test to what's left in order to get a list of potential zeroes to try:
From experience (mostly by having worked extra homework problems), I've learned that most of these exercises have their zeroes somewhere near the middle of the list, rather than at the extremes. This isn't always true, of course, but it's usually better to stay away from the larger numbers, at least when I'm getting started.
So, in this case, I won't start off by trying stuff like x = –24 or x = 12. Instead, I'll start out with smaller values like x = 2.
And I can narrow down my options further by 'cheating' and looking at the graph:
This is a fourth-degree polynomial, so it has, at most, four x-intercepts, and I can see all four of them on the graph. This means that I won't have any complex-valued zeroes.
It looks like one of the zeroes is around –3.5, but –7/2 isn't on the list that the Rational Roots Test gave me, so this must be an irrational root. I'll leave it until the end, when I'll be applying the Quadratic Formula.
It also looks like there may be zeroes near –1.5 and 0.5. But the clearest solution looks to be at x = 4 and since whole numbers are easier to work with than fractions, x = 4 would probably be a good next value to try:
The zero remainder (at the far right of the bottom row) tells me that x = 4 is indeed a root. And the bottom row of the synthetic division tells me that I'm now left with solving the following:
Looking at the constant term '6' in the polynomial above, and with the Rational Roots Test in mind, I can see that the following values:
x = ±24, ±12, ±8, –4
..from my original application of the Rational Roots Test won't work for the current polynomial. Even if I didn't already know this from having checked the graph, I can see that they won't fit with the new polynomial's leading coefficient and constant term. So I can cross these values off of my list now.
(Always check the list of possible zeroes as you go. The Rational Roots Test will sometimes give a very long list of possibilities, and it can be helpful to notice that some of those values can be ignored, especially if you don't have a graphing calculator to 'cheat' with.)
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Comparing the remaining values from the list with the intercepts on the graph, I'll try x = 1/2:
The remainder isn't zero, so that test root didn't work. This means that the zero close to x = 1/2 on the graph must be irrational. I'll find it when I apply the Quadratic Formula later on.
For now, I'll try x = –3/2:
The division came out evenly (that is, it had a zero remainder), so x = –3/2 is another of the zeroes. And after this division, I'm now left with the following polynomial equation still to solve:
2x2 + 6x – 4 = 0
Dividing through by 2 to get smaller numbers gives me:
I can apply the Quadratic Formula to this:
This gives me the remaining two roots of the original polynomial function. (I plugged the exact values into my calculator, to confirm that they match up with what I'd already seen on the graph, so I'd be certain that my answer was correct. I won't hand in these approximations, though.)
My complete answer is:
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Asking you to find the zeroes of a polynomial function, y equals (polynomial), means the same thing as asking you to find the solutions to a polynomial equation, (polynomial) equals (zero). The zeroes of a polynomial are the values of x that make the polynomial equal to zero. Either task may be referred to as 'solving the polynomial'.
So the above problem could have been stated along the lines of:
Find the solutions to 2x5 + 3x4 – 30x3 – 57x2 – 2x + 24 = 0
..or:
Find the solutions to 2x5 + 3x4 – 30x3 – 57x2 – 2x = –24
..and the answers would have been the exact same list of x-values.
URL: https://www.purplemath.com/modules/solvpoly.htm
