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30S Applied Math Mr. Knight – Killarney School Slide 1 Unit: Linear Programming Lesson 5: Problem Solving Problem Solving with Linear Programming Learning Outcome B-1 LP-L5 Objectives: To solve complex problems using Linear Programming techniques.

30S Applied Math Mr. Knight – Killarney School Slide 1 Unit: Linear Programming Lesson 5: Problem Solving Problem Solving with Linear Programming Learning

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Page 1: 30S Applied Math Mr. Knight – Killarney School Slide 1 Unit: Linear Programming Lesson 5: Problem Solving Problem Solving with Linear Programming Learning

30S Applied MathMr. Knight – Killarney School

Slide 1

Unit: Linear ProgrammingLesson 5: Problem Solving

Problem Solving with Linear Programming

Learning Outcome B-1

LP-L5 Objectives: To solve complex problems using Linear Programming techniques.

Page 2: 30S Applied Math Mr. Knight – Killarney School Slide 1 Unit: Linear Programming Lesson 5: Problem Solving Problem Solving with Linear Programming Learning

30S Applied MathMr. Knight – Killarney School

Slide 2

Unit: Linear ProgrammingLesson 5: Problem Solving

The process of finding a feasible region and locating the points

that give the minimum or maximum value to a specific

expression is called linear programming. It is frequently used

to determine maximum profits, minimum costs, minimum

distances, and so on.

Theory – Intro

Page 3: 30S Applied Math Mr. Knight – Killarney School Slide 1 Unit: Linear Programming Lesson 5: Problem Solving Problem Solving with Linear Programming Learning

30S Applied MathMr. Knight – Killarney School

Slide 3

Unit: Linear ProgrammingLesson 5: Problem Solving

Graph the following system of inequalities and identify the corner points of the feasible region. Then find the values of x and y that maximize the expression M = x + 3y.

Example - Maximize the Value of a Specific Expression

x + y 6

x + 2y 8

x 2

y 1

Page 4: 30S Applied Math Mr. Knight – Killarney School Slide 1 Unit: Linear Programming Lesson 5: Problem Solving Problem Solving with Linear Programming Learning

30S Applied MathMr. Knight – Killarney School

Slide 4

Unit: Linear ProgrammingLesson 5: Problem Solving

Graph the following system of inequalities and identify the corner points of the feasible region. Then find the values of x and y that maximize the expression M = x + 3y.

Example - Maximize the Value of a Specific Expression

x + y 6

x + 2y 8

x 2

y 1

Solution1. Graph the system: The feasible region is the green shaded area shown 2. Find the vertices of the feasible region: The coordinates of the corner points are (2, 3), (2, 1), (5, 1), and (4, 2).3. Substitute each vertice into the equation to find maximum: The value of M for each point is

Point (2, 3): M = 2 + 3(3) = 11Point (2, 1): M = 2 + 3(1) = 5Point (5, 1): M = 5 + 3(1) = 8Point (4, 2): M = 4 + 3(2) = 10

Therefore, the value of M is maximized at (2, 3).

Page 5: 30S Applied Math Mr. Knight – Killarney School Slide 1 Unit: Linear Programming Lesson 5: Problem Solving Problem Solving with Linear Programming Learning

30S Applied MathMr. Knight – Killarney School

Slide 5

Unit: Linear ProgrammingLesson 5: Problem Solving

Graph the following system of inequalities and identify the corner points of the feasible region. Then find the values of x and y that maximize the expression M = 4x + y.

Test Yourself - Maximize the Value of a Specific Expression

x 0y 0

3x + 2y 62x + 3y 6

Page 6: 30S Applied Math Mr. Knight – Killarney School Slide 1 Unit: Linear Programming Lesson 5: Problem Solving Problem Solving with Linear Programming Learning

30S Applied MathMr. Knight – Killarney School

Slide 6

Unit: Linear ProgrammingLesson 5: Problem Solving

Graph the following system of inequalities and identify the corner points of the feasible region. Then find the values of x and y that maximize the expression M = 4x + y.

Test Yourself - Maximize the Value of a Specific Expression

x 0y 0

3x + 2y 62x + 3y 6

Solution1. Graph the system: The feasible region is the green shaded area shown 2. Find the vertices of the feasible region: The coordinates of the corner points are (0, 3), (0, 2), and (1.2, 1.2).3. Substitute each vertice into the equation to find maximum: Using (0, 3), M = 4(0) + 3 = 3.Using (0, 2), M = 4(0) + 2 = 2.Using (1.2, 1.2), M = 4(1.2) + 1.2 = 6.

The coordinates (1.2, 1.2) produce the maximum value of the expression 4x + y.

Page 7: 30S Applied Math Mr. Knight – Killarney School Slide 1 Unit: Linear Programming Lesson 5: Problem Solving Problem Solving with Linear Programming Learning

30S Applied MathMr. Knight – Killarney School

Slide 7

Unit: Linear ProgrammingLesson 5: Problem Solving

Graph the following system of inequalities and identify the corner points of the feasible region. Then find the values of x and y that minimize the expression M = 3x + 2y.

Test Yourself – Minimize the Value of a Specific Expression

x + y 4x + 5y 8

-x + 2y 6

Page 8: 30S Applied Math Mr. Knight – Killarney School Slide 1 Unit: Linear Programming Lesson 5: Problem Solving Problem Solving with Linear Programming Learning

30S Applied MathMr. Knight – Killarney School

Slide 8

Unit: Linear ProgrammingLesson 5: Problem Solving

Graph the following system of inequalities and identify the corner points of the feasible region. Then find the values of x and y that minimize the expression M = 3x + 2y.

Test Yourself – Minimize the Value of a Specific Expression

x + y 4x + 5y 8

-x + 2y 6

Solution1. Graph the system: The feasible region is the green shaded area shown 2. Find the vertices of the feasible region: The coordinates of the corner points are (-2, 2), (3, 1), and (0.67, 3.33).3. Substitute each vertice into the equation to find minimum: Using (-2, 2), M = 3(-2) + 2(2) = -2.Using (3, 1), M = 3(3) + 2(1) = 11.Using (0.67, 3.33), M = 3(0.67) + 2(3.33) = 8.67.

The coordinates (-2, 2) produce the minimum value of the expression 3x + 2y.

Page 9: 30S Applied Math Mr. Knight – Killarney School Slide 1 Unit: Linear Programming Lesson 5: Problem Solving Problem Solving with Linear Programming Learning

30S Applied MathMr. Knight – Killarney School

Slide 9

Unit: Linear ProgrammingLesson 5: Problem Solving

The constraints for manufacturing two types of hockey skates are given by the following system of inequalities. Find the maximum value of Q over the feasible region if Q = 3x + 5y.

Test Yourself – Maximize the Value of a Specific Expression

y -1x + 4x + 4y 7

-x + 2y 5

Page 10: 30S Applied Math Mr. Knight – Killarney School Slide 1 Unit: Linear Programming Lesson 5: Problem Solving Problem Solving with Linear Programming Learning

30S Applied MathMr. Knight – Killarney School

Slide 10

Unit: Linear ProgrammingLesson 5: Problem Solving

The constraints for manufacturing two types of hockey skates are given by the following system of inequalities. Find the maximum value of Q over the feasible region if Q = 3x + 5y.

Test Yourself – Maximize the Value of a Specific Expression

y -1x + 4x + 4y 7

-x + 2y 5

Solution1. Graph the system: The feasible region is the green shaded area shown 2. Find the vertices of the feasible region: The coordinates of the corner points are (1, 3), (-1, 2), and (3, 1).3. Substitute each vertice into the equation to find maximum: Using (1, 3), Q = 3(1) + 5(3) = 18.Using (-1, 2), Q = 3(-1) + 5(2) = 7.Using (3, 1), Q = 3(3) + 5(1) = 14.

The coordinates (1, 3) produce a maximum value for Q over the feasible region where Q = 3x + 5y.

Page 11: 30S Applied Math Mr. Knight – Killarney School Slide 1 Unit: Linear Programming Lesson 5: Problem Solving Problem Solving with Linear Programming Learning

30S Applied MathMr. Knight – Killarney School

Slide 11

Unit: Linear ProgrammingLesson 5: Problem Solving

Here is a plan of the steps used to solve word problems using linear programming:

1. After reading the question, make a chart to see the information more clearly.

2. Assign variables to the unknowns.

3. Form expressions to represent the restrictions.

4. Graph the inequalities.

5. Find the coordinates of the corner points of the feasible region.

6. Find the vertex point that maximizes or minimizes what we are looking for.

7. State the solution in a sentence.

Theory – Solving Problems Using Linear Programming

Page 12: 30S Applied Math Mr. Knight – Killarney School Slide 1 Unit: Linear Programming Lesson 5: Problem Solving Problem Solving with Linear Programming Learning

30S Applied MathMr. Knight – Killarney School

Slide 12

Unit: Linear ProgrammingLesson 5: Problem Solving

Example – Seven Steps

Page 13: 30S Applied Math Mr. Knight – Killarney School Slide 1 Unit: Linear Programming Lesson 5: Problem Solving Problem Solving with Linear Programming Learning

30S Applied MathMr. Knight – Killarney School

Slide 13

Unit: Linear ProgrammingLesson 5: Problem Solving

Example – Seven Steps cont’d

Page 14: 30S Applied Math Mr. Knight – Killarney School Slide 1 Unit: Linear Programming Lesson 5: Problem Solving Problem Solving with Linear Programming Learning

30S Applied MathMr. Knight – Killarney School

Slide 14

Unit: Linear ProgrammingLesson 5: Problem Solving

Example – Seven Steps cont’d

Page 15: 30S Applied Math Mr. Knight – Killarney School Slide 1 Unit: Linear Programming Lesson 5: Problem Solving Problem Solving with Linear Programming Learning

30S Applied MathMr. Knight – Killarney School

Slide 15

Unit: Linear ProgrammingLesson 5: Problem Solving

Example 2 – Seven Steps

Page 16: 30S Applied Math Mr. Knight – Killarney School Slide 1 Unit: Linear Programming Lesson 5: Problem Solving Problem Solving with Linear Programming Learning

30S Applied MathMr. Knight – Killarney School

Slide 16

Unit: Linear ProgrammingLesson 5: Problem Solving

Example 2 – Seven Steps cont’d

Page 17: 30S Applied Math Mr. Knight – Killarney School Slide 1 Unit: Linear Programming Lesson 5: Problem Solving Problem Solving with Linear Programming Learning

30S Applied MathMr. Knight – Killarney School

Slide 17

Unit: Linear ProgrammingLesson 5: Problem Solving

Example 2 – Seven Steps cont’d