Math Problem Statement
Answer this and make a solution
Solution
To solve the problem presented in the image using Linear Programming (LP), let’s break it down step-by-step. We need to help Axis maximize his pleasure by allocating his study and play time, subject to some constraints.
Step 1: Define Variables
Let:
- represent the number of hours Axis spends studying.
- represent the number of hours Axis spends playing.
Step 2: Objective Function
The problem says that play is twice as enjoyable as studying, so we can define the objective function to maximize his total pleasure. Since play is twice as enjoyable as study, the total pleasure function will be: Where:
- is the study time.
- is the play time.
We want to maximize .
Step 3: Constraints
The problem provides several constraints:
- Axis has a total of 10 hours to allocate between study and play:
- He wants to study at least as much as he plays, so:
- Axis can’t play more than 4 hours a day:
- Both and must be non-negative:
Step 4: Formulate the Linear Program
We are now ready to formulate the Linear Program: subject to:
Step 5: Graphing and Solving the Linear Program
To solve this LP problem, we can graph the constraints and find the feasible region. Then, we evaluate the objective function at the corner points of the feasible region.
Feasible Region:
- The inequality is a line with slope -1. It will cut off the area to the left and below the line.
- The inequality means we are above or on the line , which is a 45-degree diagonal line.
- The inequality represents a horizontal line at .
We would graph these lines and find the intersection points to evaluate the objective function.
Step 6: Evaluate Objective Function at Corner Points
After graphing the constraints, find the corner points of the feasible region. Then, plug those points into the objective function to determine the maximum value.
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Math Problem Analysis
Mathematical Concepts
Linear Programming
Optimization
Objective Functions
Inequalities
Formulas
P = x + 2y
x + y <= 10
x >= y
y <= 4
x >= 0
y >= 0
Theorems
Maximization of Objective Function
Graphing Constraints
Linear Programming Theorem
Suitable Grade Level
Grades 11-12
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