Optimization Calculator (Max/Min Problems) | High School AP Calculus Solver

Optimization (Max/Min) Calculator

High School Optimization (Max/Min) Calculator

Find local maxima and minima of a function using calculus derivatives.

Try: x^3 – 3x, sin(x), x^4 – 2x^2

Derivative f'(x)

Critical Points Found

Waiting for calculation…

Optimization Graph

f(x)
Maxima
Minima

About the Optimization (Max/Min) Calculator

Optimization is one of the most useful applications of calculus. It involves finding the absolute maximum or minimum values of a function, which corresponds to the “best” outcome in real-world scenarios—such as maximizing profit, minimizing cost, or optimizing surface area for a given volume.

Critical Points & Derivatives

The peaks (maxima) and valleys (minima) of a smooth graph occur where the tangent line is horizontal. This means the slope of the curve is zero.
To find these points algebraically:

  1. Find the derivative f'(x).
  2. Set f'(x) = 0 and solve for x. These x-values are called Critical Points.
  3. Use the First Derivative Test (checking sign changes) or Second Derivative Test to classify them as max or min.

Global vs. Local Extrema

A local maximum is the highest point in its immediate neighborhood. A global maximum is the highest point on the entire domain of the function. This Optimization (Max/Min) Calculator focuses on identifying local extrema within the viewing window you specify.

FAQ

Is this Optimization (Max/Min) Calculator free?

Yes, this tool is completely free and runs in your browser using JavaScript.

Why didn’t it find all points?

The calculator scans numerically within the “View Interval” you set. If a maximum is outside this range (e.g., at x=100), it won’t be detected. Expand your interval to see more.

Does the Optimization (Max/Min) Calculator handle inflection points?

It specifically looks for maxima and minima (slope = 0). Points of inflection (where concavity changes) are not currently highlighted unless the slope is also zero there.

How accurate is it?

It uses a numerical scan with high precision, but extremely steep functions or tiny oscillations might result in approximations.

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