Every gram of wheat provides 0.1 g of proteins and 0.25 g of carbohydrates. The corresponding values of rice are 0.05 g and 0.5 g respectively. Wheat costs ? 4 per kg and rice ? 6. The minimum daily requirements of proteins and carbohydrates for an average child are 50 g and 200 g respectively. Then in what quantities should wheat and rice be mixed in the daily diet to provide minimum daily requirement of proteins and carbohydrates at minimum cost
Updated On: Jul 5, 2022
400, 200
300, 400
200, 400
400, 300
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The Correct Option isA
Solution and Explanation
Suppose $x$ grams of wheat and $y$ grams of rice are mixed in the daily diet.
Since every grams of wheat provides $0.1 g$ of proteins and every gram of rice gives $0.05 g$ of proteins. Therefore, $x$ gms of wheat and $y$ grams of rice will provide $0.1x + 0.05y$ g of proteins. But the minimum daily requirement of proteins is of $50 g$.
$\therefore\quad0.1x + 0.05y \ge 50\quad\Rightarrow\quad \frac{x}{10}+ \frac{y}{20} \ge 50$
Similarly, $x$ grams of wheat and $y$ grams of rice will provide $0.25x + 0.5y$ g of carbohydrates and the minimum daily requirement of carbohydrates is of $200 g$.
$\therefore\quad0.25x + 0.5y \ge 200\quad\Rightarrow\quad \frac{x}{4}+ \frac{y}{2} \ge 200$
Since, the quantities of wheat and rice cannot be negative.
Therefore,$\quad $x$ \ge 0,\quad y \ge 0$
It is given that wheat costs ? $4$ per kg and rice ? $6$ per kg. So, $x$ grams of wheat and $y$ grams of rice will cost
$\quad ? \frac{4x}{1000} + \frac{6y}{1000}$
Subject to the constraints
$\frac{x}{10} + \frac{y }{20} \ge 50, \frac{x}{4} + \frac{y}{2} \ge 200,\quad$ and $x \ge 0, y \ge 0$
The solution set of the linear constraints is shaded in figure. The vertices of the shaded region are
$A_2 (800, \,0), \,P \,(400,\, 200)$ and $B_1(0,\, 1000)$.
The values of the objective function at these points are given in the following table.
Clearly, $Z$ is minimum for $x = 400$ and $y = 200$. The minimum diet cost is $2.8.$
Linear programming is a mathematical technique for increasing the efficiency and effectiveness of operations under specific constraints. The main determination of linear programming is to optimize or minimize a numerical value. It is built of linear functions with linear equations or inequalities restricting variables.
Characteristics of Linear Programming:
Decision Variables: This is the first step that will determine the output. It provides the final solution to the problem.
Constraints: The mathematical form in which drawbacks are expressed, regarding the resource.
Data: They are placeholders for known numbers to make writing complex models simple. They are constituted by upper-case letters.
Objective Functions: Mathematically, the objective function should be quantitatively defined.
Linearity: The function's relation between two or more variables must be straight. It indicates that the variable's degree is one.
Finiteness: Input and output numbers must be finite and infinite. The best solution is not possible if the function consists infinite components.
Non-negativity: The value of the variable should be either positive (+ve) or 0. It can't be a negative (-ve) number.