The optimal length is ft.
The optimal width is ft.
The maximum area is sq. ft.
We find extremes of functions which model real world situations.
Optimization
Maximize the objective subject to the constraint To find the maximum area, we need to eliminate one of the variables from the objective function. We use the constraint to do this. Solve the constraint for either or . In this case, solving the constraint for gives We substitute this expression of into the objective function to get Since represents a length of fence, we have . Furthermore, since we have 2400 feet of fence which implies . Thus we would like find the absolute maximum of on the interval . Since is a continuous function, the EVT says that it has an abs max on the closed interval . We use the closed interval method of section 3.1 to find the abs max.
The critical numbers are: which yields which is in the interval. Comparing values, we have and . Thus the abs max occurs when .
We can also note that gives a maximum since the graph of is a parabola that opens down.
We next find by plugging into the constraint: Finally the maximum area of the enclosure is
The optimal length is ft.
The optimal width is ft.
The maximum area is sq. ft.
river
The optimal length is ft.
The optimal width is ft.
The maximum area is sq. ft.
Let the two numbers be and and let their product be .
The objective equation is .
The constraint equation is .
The maximum value of the product is .
If we let represent the length and width of the box, and its height, then our objective is to maximize the volume,
We have a material constraint which says that the surface area of the box should be 4800 sq. in: Solving the constraint for gives Substituting this into the objective gives: where . Simplifying gives: The volume will be at a maximum when its derivative is zero: Solving for , we get: Since is not in the interval , we eliminate it from consideration. Furthermore, since and (since in this case), the maximum volume occurs when . Plugging this into the constraint equation, we can find : Thus the volume is maximized when and and the maximum volume of the box is:
The optimal length and width are inches.
The optimal height is inches.
The maximum volume is cubic inches.
In some problems, the objective function involves a composition, . If the outsode function is strictly increasing, then the max or min of the composition occurs at the same -value as the max/min of . We will see this in the next example.
To solve this problem, we need the formula for the distance between two points in a plane. If the points are and , then the Pythagorean Theorem gives the distance between them:
We apply the distance formula to the comet at the point and the sun at the origin to get the objective equation: Since the comet must stay on the parabola we get the constraint equation . Substituting this into the objective equation gives: Now, we would like to find the minimum value of . Since the square root function is increasing, we can locate the minimum by finding the min of the radicand (the quantity under the square root). So, we want to minimize The minimum occurs when the derivative is zero, so we solve for yielding which gives either The three solutions are . The corresponding -values can be found by plugging these -values into the parabola giving the three points If the comet is at then its distance to the sun is 5 million miles. If the comet is at either then the distance is Hence the minimum distance is million miles when the comet is at either of the points .
The comet is closest to the sun at two points. The x-coordinates of these points are
(in ascending order)
and .
The minimum distance is million miles.
Let be the length of the enclosure and the width. Because of the partitions, there are 3 horizontal and 3 vertical sections of fence. Hence the total amount of fence needed can be expressed as This is our objective function. Since the area of the enclosure needs to be 1600 sq. ft., we have the constraint Solving the constraint for gives Substituting this into the objective yields To find the minimum value of , we solve . This gives which means and so ft. Since from context, we have ft. as our solution. Plugging this value of into the constraint equation gives So the solution is for the gardener to build a square, 40 feet on a side, using a total of feet of fence.
The optimal length is ft.
The optimal width is ft.
The minimum amount of fence needed is ft.
Let meters be the distance that the cheetah walks and meters the distance that the cheetah swims, as shown in the figure below.
The total time for the trip is the time walking plus the time swimming. Since the total time is This is the objective equation. The constraint comes from the Pythagorean Theorem, since the swim portion of the trip is along the hypotenuse of a right triangle with legs parallel and perpendicular to the river bank. One leg of the triangle is and the other is . So Substituting this into the objective gives: where is between and . To find the minimum value of , we find the critical numbers (using the chain rule):
Solving for gives Square both sides: Hence To verify that this is indeed the minimum time, we can use the closed interval method from section 3.2 (Extreme Value Theorem). This is because our independent variable must be between and . Thus we compare and . We have Hence the minimum time to reach the prey is approximately seconds and this is achieved by walking approximately meters, then swimming the rest of the way.
The minimum amount of time to reach her destination (to 2 decimal places) is hours.