Question:

An oil company required 12000, 20000 and 15000 barrels of high-grade, medium grade and low grade oil, respectively. Refinery A produces 100, 300 and 200 barrels per day of high-grade, medium-grade and low-grade oil, respectively, while refinery B produces 200, 400 and 100 barrels per day of high-grade, medium-grade and low-grade oil, respectively. If refinery A costs ? 400 per day and refinery B costs ? 300 per day to operate, then the days should each be run to minimize costs while satisfying requirements are

Updated On: Jul 5, 2022
  • 30, 60
  • 60, 30
  • 40, 60
  • 60, 40
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The Correct Option is B

Solution and Explanation

The given data may be put in the following tabular form Suppose refineries A and B should run for x and y days respectively to minimize the total cost. The mathematical form of the above is Minimize $Z = 400x + 300y$ Subject to $100x + 200y \ge 12000$ $300x + 400y \ge 20000$ $200x + 100y \ge 15000$ and $x, y \ge 0$ The feasible region of the above LPP is represented by the shaded region in the given figure. The corner points of the feasible region are $A_2(120, 0), P(60, 30)$ and $B_3(0, 1 50)$. The value of the objective function at these points are given in the following table
Clearly, $Z$ is minimum when $x = 60, y = 30.$ Hence, the machine $A$ should run for $60$ days and the machine$ B$ should run for $30$ days to minimize the cost while satisfying the constraints.
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Concepts Used:

Linear Programming

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.