We encounter numerous problems in our daily lives, spanning disciplines like biology, economics, physics, and sociology. When these real-world problems are translated into mathematical terms to find a solution, the process is known as Mathematical Modelling.
Historical Chronicle: The Origins of Systemic Modelling
Mathematical modelling is a structured, iterative process. It involves four fundamental sequential phases:
This is the transition from a real-world problem to a mathematical abstraction.
Once the mathematical equations are formed, we use algebraic, geometric, or calculus-based methods to solve them.
The mathematical solutions obtained in Phase 2 must be translated back into the context of the original real-world problem.
The interpreted results are compared with actual real-world data or observations.
Mathematical Problem Statement: Formulate a model to calculate the amount $A$ after $n$ years if a principal $P$ is invested at an annual interest rate $r$ (in percentage) compounded annually.
Step-by-Step Algorithmic Solution Trace:
- Formulation: Let the initial principal be $P$. The interest after the first year is $I_1 = P \times \frac{r}{100}$.
- Amount after 1st year: $A_1 = P + P\left(\frac{r}{100}\right) = P\left(1 + \frac{r}{100}\right)$.
- Amount after 2nd year: The new principal is $A_1$.$$A_2 = A_1 \left(1 + \frac{r}{100}\right) = P\left(1 + \frac{r}{100}\right)\left(1 + \frac{r}{100}\right) = P\left(1 + \frac{r}{100}\right)^2$$
- Generalizing for $n$ years via inductive reasoning gives the model:$$A = P\left(1 + \frac{r}{100}\right)^n$$
Final Evaluation Output: The mathematical model for compound interest is $A = P\left(1 + \frac{r}{100}\right)^n$.
Mathematical Problem Statement: A manufacturer wants to construct a cylindrical can to hold $1000\text{ cm}^3$ of oil. Find the dimensions that minimize the cost of the metal to construct the can.
Step-by-Step Algorithmic Solution Trace:
- Formulation: Let $r$ be the radius and $h$ be the height. Volume $V = \pi r^2 h = 1000$. Surface Area $S = 2\pi r^2 + 2\pi r h$.
- Express $h$ in terms of $r$:$$h = \frac{1000}{\pi r^2}$$
- Substitute $h$ into the Surface Area function to create a single-variable model:$$S(r) = 2\pi r^2 + 2\pi r \left(\frac{1000}{\pi r^2}\right) = 2\pi r^2 + \frac{2000}{r}$$
- Solution (Calculus): Differentiate $S$ with respect to $r$ to find the critical point:$$S'(r) = 4\pi r - \frac{2000}{r^2} = 0 \implies 4\pi r^3 = 2000 \implies r = \sqrt[3]{\frac{500}{\pi}} \approx 5.42\text{ cm}$$
- Calculate $h$:$$h = \frac{1000}{\pi (5.42)^2} \approx 10.84\text{ cm}$$
- Interpretation & Validation: The dimensions that minimize the surface area (and thus material cost) occur when the height is equal to the diameter ($h = 2r$).
Final Evaluation Output: Optimal dimensions: $r \approx 5.42\text{ cm}$ and $h \approx 10.84\text{ cm}$.