Linear Programming Unit 2, Lesson 4 10/13.

Slides:



Advertisements
Similar presentations
Solve the system of inequalities by graphing. x ≤ – 2 y > 3
Advertisements

3.4 Linear Programming.
3.4 Linear Programming 10/31/2008. Optimization: finding the solution that is either a minimum or maximum.
Linear Programming 1.6 (M3) p. 30 Test Friday !!.
Ch 2. 6 – Solving Systems of Linear Inequalities & Ch 2
Linear Programming?!?! Sec Linear Programming In management science, it is often required to maximize or minimize a linear function called an objective.
Objectives: Set up a Linear Programming Problem Solve a Linear Programming Problem.
Linear Programming Digital Lesson. Copyright © by Houghton Mifflin Company, Inc. All rights reserved. 2 Linear programming is a strategy for finding the.
Algebra 2 Chapter 3 Notes Systems of Linear Equalities and Inequalities Algebra 2 Chapter 3 Notes Systems of Linear Equalities and Inequalities.
Algebra 2 Chapter 3 Notes Systems of Linear Equalities and Inequalities Algebra 2 Chapter 3 Notes Systems of Linear Equalities and Inequalities.
Copyright 2013, 2010, 2007, Pearson, Education, Inc. Section 7.6 Linear Programming.
3.4 Linear Programming p Optimization - Finding the minimum or maximum value of some quantity. Linear programming is a form of optimization where.
P I can solve linear programing problem. Finding the minimum or maximum value of some quantity. Linear programming is a form of optimization where.
Solve problems by using linear programming.
Opener. Notes: 3.4 Linear Programming Optimization  Many real-life problems involve a process called optimization.  This means finding a maximum or.
Linear Programming: A Geometric Approach3 Graphing Systems of Linear Inequalities in Two Variables Linear Programming Problems Graphical Solution of Linear.
3.5 Linear Programming Warm-up (IN) 1. Solve the system: (5, 2)
Linear Programming Problem. Definition A linear programming problem is the problem of optimizing (maximizing or minimizing) a linear function (a function.
Warm-Up 3.4 1) Solve the system. 2) Graph the solution.
5 minutes Warm-Up 1) Solve the system. 2) Graph the solution.
Class Schedule: Class Announcements Homework Questions 3.4 Notes Begin Homework.
Monday WARM-UP: TrueFalseStatementCorrected Statement F 1. Constraints are conditions written as a system of equations Constraints are conditions written.
3.4 – Linear Programming. Ex. 1 Graph the system of inequalities. Name the coordinates of the vertices of the feasible region. Find the max & min values.
3.4: Linear Programming Objectives: Students will be able to… Use linear inequalities to optimize the value of some quantity To solve linear programming.
Class Opener: Solve each equation for Y: 1.3x + y = y = 2x 3.x + 2y = 5 4. x – y = x + 3y = x – 5y = -3.
Warm-up Solve each system of equations:
Get out your Vertices Worksheet!
Review Homework Page Rocket City Math League There are five levels of three rounds of individual testing that range from Pre-Algebra to Calculus,
3-4 Linear Programming (p. 139) Algebra 2 Prentice Hall, 2007.
Constraints Feasible region Bounded/ unbound Vertices
Unit 1 Linear programming. Define: LINEAR PROGRAMMING – is a method for finding a minimum or maximum value of some quantity, given a set of constraints.
Warm-upWarm-up Sketch the region bounded by the system of inequalities: 1) 2) Sketch the region bounded by the system of inequalities: 1) 2)
LINEAR PROGRAMMING 3.4 Learning goals represent constraints by equations or inequalities, and by systems of equations and/or inequalities, and interpret.
1 What you will learn  Lots of vocabulary!  How to find the maximum and minimum value of a function given a set of “rules”
3-4: Linear Programming Objectives: Standards addressed:
3-5: Linear Programming. Learning Target I can solve linear programing problem.
Linear Programming. What is linear programming? Use a system of constraints (inequalities) to find the vertices of the feasible region (overlapping shaded.
3.4 Linear Programming Objective:
3.3 Linear Programming. Vocabulary Constraints: linear inequalities; boundary lines Objective Function: Equation in standard form used to determine the.
Chapter 3 Section 4 Linear Programming Algebra 2 January 29, 2009.
1. What does a need to be if there were infinitely many solutions to the system of equations. y + 2x = 12 2y + 4x = 2a.
Section 3.5 Linear Programing In Two Variables. Optimization Example Soup Cans (Packaging) Maximize: Volume Minimize: Material Sales Profit Cost When.
3.4 Linear Programming p Optimization - Finding the minimum or maximum value of some quantity. Linear programming is a form of optimization where.
LINEAR PROGRAMMING A-CED.3 REPRESENT CONSTRAINTS BY EQUATIONS OR INEQUALITIES, AND BY SYSTEMS OF EQUATIONS AND/OR INEQUALITIES, AND INTERPRET SOLUTIONS.
HW: Pg #10-14, 15-21o 10. Min of -34 at (-2, -6); Max of 27 at (1, 5) 11. Min of 10 at (2, 1); No Max – feasible region is unbounded 12. Min of.
Linear Programming Chapter 3 Lesson 4 Vocabulary Constraints- Conditions given to variables, often expressed as linear inequalities. Feasible Region-
October 7: Systems of Equations Today you will review how to solve systems of equations by graphing and will learn how to classify the systems. - HW Review.
2.6 Solving Systems of Linear Inequalities
2.7 Linear Programming Objectives: Use linear programming procedures to solve applications. Recognize situations where exactly one solution to a linear.
Digital Lesson Linear Programming.
2-7 Linear Programming Pre Calc A.
Digital Lesson Linear Programming.
Math 1 Warm Up In the Practice Workbook… Practice 7-6 (p. 94)
ALGEBRA II HONORS/GIFTED SECTION 3-4 : LINEAR PROGRAMMING
Linear Systems Chapter 3.
3.2 Linear Programming 3 Credits AS
3-3 Optimization with Linear Programming
Linear Programming.
Linear Programming Objectives: Set up a Linear Programming Problem
3.4 – Linear Programming.
8.4 Linear Programming p
3.2 Linear Programming 3 Credits AS
Graphing Systems of Linear Inequalities
3.4b: Linear Programming ~ Application
Copyright © 2014, 2010, 2007 Pearson Education, Inc.
LINEARPROGRAMMING 4/26/2019 9:23 AM 4/26/2019 9:23 AM 1.
Nature does nothing uselessly.
Section Linear Programming
1.6 Linear Programming Pg. 30.
Presentation transcript:

Linear Programming Unit 2, Lesson 4 10/13

Warmup Have your homework problem(s) out on your desk. Pick up a sheet of graph paper from the front table. Graph the following systems of inequalities & STATE 2 SOLUTIONS: 1. y < -2x – 4 & y ≥ 3x + 1 2. y > 2 3 x – 4, y ≤ −1 5 x + 4, and x > 0

Key Terms Optimization – finding the maximum or minimum value of some quantity Linear Programming – the process of optimizing an objective function Objective function – the equation used to find the maximum or minimum value Constraints – the system of inequalities that defines where the max or min can occur Feasible region – the graph of the constraints Vertex (vertices) – the most important values of the feasible region

Solutions in Linear Programming If an objective function has a maximum or minimum value, it MUST occur at a vertex of the feasible region. If the feasible region is bounded, the objective function will have BOTH a maximum and a minimum value.

Feasible Regions Bounded Unbounded

Finding Max/Min Values Graph the constraints Identify the feasible region Find all the vertices of the feasible region Substitute the coordinates of each vertex into the objective function Determine the max and/or min values

Example Obj. Function: C = 3x + 4y Constraints: x ≥ 0, y ≥ 0, x + y ≤ 8

Example Obj. Function: C = 5x + 6y Constraints: x ≥ 0, y ≥ 0, x + y ≥ 5, 3x + 4y ≥ 18

Your Turn Obj. Function: C = -2x + y Constraints: x ≥ 0, y ≥ 0, x + y ≥ 7, 5x + 2y≥ 20

Problem 1: Porscha’s Cupcake Shop 1.) What are we trying to find? 3.) Equations by topic: 5.) Hidden constraints? 7.) Vertices of feasible region: 2.) Define variables: Let x = __________ Let y = __________ 4.) Constraints: 6.) Graph the feasible region: 8.) Test each vertex in both equations.

Problem 2: Taking a Test 1.) What are we trying to find? 3.) Equations by topic: 5.) Hidden constraints? 7.) Vertices of feasible region: 2.) Define variables: Let x = __________ Let y = __________ 4.) Constraints: 6.) Graph the feasible region: 8.) Test each vertex in both equations.

Exit Ticket A company produces packs of pencils and pens. The company produces at least 100 packs of pens each day, but no more than 240. The company produces at least 70 packs of pencils each day, but no more than 170. A total of less than 300 packs of pens and pencils are produced each day. Each pack of pens makes a profit of $1.25. Each pack of pencils makes a profit of $0.75. What is the maximum profit the company can make each day?