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QM B Linear Programming

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QM B Linear Programming. Overview. What is linear programming (LP)? Formulating LPs The Stratton company Graphical insight Using Excel Solver to solve LPs Mile-High Microbrewery. What is linear programming?. It is NOT computer programming. Programming here means planning. - PowerPoint PPT Presentation
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QM B Linear Programming
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Page 1: QM B Linear Programming

QM B Linear Programming

Page 2: QM B Linear Programming

Overview

• What is linear programming (LP)?

• Formulating LPs– The Stratton company

• Graphical insight

• Using Excel Solver to solve LPs– Mile-High Microbrewery

Page 3: QM B Linear Programming

What is linear programming?• It is NOT computer programming.

Programming here means planning.• Mathematical technique• Optimization technique

– A decision needs to made– Our goal is to determine the ‘best’ or

‘optimum’ decision– There are scarce resources available

and/or specified requirements for achieving our goal.

Page 4: QM B Linear Programming

Proctor and GambleNorth American Product Sourcing

– 50 products– 60 plants– 10 distribution centers– 1000 customer zones– Save $200 million dollars annually– Which products should be produced in

which plants?– Which plants should supply which

distribution centers?– Which distribution centers should supply

which customer zones.

Page 5: QM B Linear Programming

What does an LP look like?

• There is a goal: objective function – Maximized or minimized – Written as a linear equation

• There are scarce resources, restrictions and/or requirements: constraints– Limits your ability to achieve the goal– Written as a linear equation

Page 6: QM B Linear Programming

Formulating an LP: Stratton Co.

• Produces two basic types of plastic pipes

• Three resources have been identified as critical to pipe output– Pipe extrusion hours– Packaging hours– Special additive mix

Page 7: QM B Linear Programming

Stratton Company Data

ProductResource Availability

Resource Type 1

Type 2

Extrusion 4 hrs. 6 hrs. 48 hrs.

Packaging 2 hrs. 2 hrs. 18 hrs.

Additive Mix

2 lbs. 1 lbs. 16 lbs.

Profit $34 $40All data given is for a package of pipe – 100 feet

Page 8: QM B Linear Programming

Stratton Company (cont)

Formulate an LP model to determine how much of each type of pipe should be produced to maximize profit.

Page 9: QM B Linear Programming

Three questions to formulate an LP:

• What is the decision to be made?– Stratton Company

• How much of pipe 1 to produce• How much of pipe 2 to produce

– Defines the variables (if you are specific enough).• P1 – number of packages of Pipe 1 to

produce• P2 – number of packages of Pipe 2 to

produce

Page 10: QM B Linear Programming

Question 2 for Formulating an LP:

• What is the goal?– Stratton Company

• Maximize profit

– Defines the objective function

MAX 34 P1 + 40 P2

Page 11: QM B Linear Programming

Question 3 for Formulating an LP:• What are the

limited resources or requirements?– Extrusion hours

– Packaging hours

– Additive mix

4P1 + 6P2 48

2P1 + 2P2 18

2P1 + 1P2 16

Page 12: QM B Linear Programming

LP for Stratton Company

MAX 34 P1 + 40 P2

Subject to:4 P1 + 6 P2 48 Extrusion hours2 P1 + 2 P2 18 Packaging hours2 P1 + 1 P2 16 Additive supply

P1 0 and P2 0 Non-negativity

Objective Function

Constraints

Page 13: QM B Linear Programming

Solving LPs• ‘What if’ analysis (go to Excel)

• Graphical analysis– For insight

• Simplex method– Solver – an Excel add-in– Computer packages designed for linear

optimization

Page 14: QM B Linear Programming

Graphical analysis – non-negativity

P1P

2

P1 NegativeP2 Positive

P1 NegativeP2 Negative

P1 PositiveP2 Negative

P1 - PositiveP2 - Positive

Page 15: QM B Linear Programming

Graphical analysis – Extrusion constraint

Stratton Company

0123456789

0 1 2 3 4 5 6 7 8 9 10 11 12 13

P1

P2 Extrusion

4 P1 + 6 P2 48

Page 16: QM B Linear Programming

Graphical analysis – Packaging Constraint

Stratton Company

0123456789

10

0 1 2 3 4 5 6 7 8 9 10 11 12 13

P1

P2 Extrusion

Packaging

2 P1 + 2 P2 18

Page 17: QM B Linear Programming

Graphical analysis – Additive supply constraint

Stratton Company

0

2

4

6

8

10

12

14

16

18

0 1 2 3 4 5 6 7 8 9 10 11 12 13

P1

P2

Extrusion

Packaging

Additive Supply

2 P1 + 1 P2 16

Feasible Region

Page 18: QM B Linear Programming

Feasible Region

• Set of all solutions that satisfy all of the constraints

• Infinite number of solutions

Which is the optimal solution?

• One of the solutions at the corner points

Page 19: QM B Linear Programming

Corner point solutionsStratton Company

0

2

4

6

8

10

12

14

16

18

0 1 2 3 4 5 6 7 8 9 10 11 12 13

P1

P2

Extrusion

Packaging

Additive Supply

Feasible Region

MAX 34 P1 + 40 P2 (go to Excel)

Page 20: QM B Linear Programming

Stratton Company – Summary

• Optimal solution– P1 = 3– P2 = 6– Max = $342

• The optimal product mix is 3 packages of Pipe 1 and 6 packages of Pipe 2. This provides a maximum profit of $342.

Page 21: QM B Linear Programming

Setting up Excel Solver to solve LPs

• Solver is an add-in to Excel– Not automatically ready– To get solver ready:

In ExcelTools -> Add insScroll down to Solver Add inCheck the boxClick on OK

• Only need to do this one time

Page 22: QM B Linear Programming

Mile-High Microbrewery

Mile-High Microbrewery makes a light beer and a dark beer. Mile-High has a limited supply of barley, limited bottling capacity, and a limited market for light beer. Profits are $0.20 per bottle of light beer and $0.50 per bottle of dark beer. Formulate an LP to maximize profits and determine how many bottles of each product should be produced per month.

Page 23: QM B Linear Programming

Mile-High Microbrewery Data

Mile-High Microbrewery

Resource

Resource Light Dark Availability

Barley (grams) 0.1 0.6 2000

Bottling (bottles) 1 1 6000

Market (bottles) 1 4000

Profi t $0.20 $0.50

Product

Page 24: QM B Linear Programming

Think-pair-share: Three questions:

• What are the decisions to be made?

• What is the goal?

• What are the limited resources or requirements?

Page 25: QM B Linear Programming

What are the decisions to be made?

• L – Number of bottles of light beer to produce

• D – Number of bottles of dark beer to produce

Page 26: QM B Linear Programming

What is the goal?

• Maximize profit

MAX 0.20 L + 0.50 D

Page 27: QM B Linear Programming

What are the limited resources or requirements?• Barley supply

0.10 L + 0.60 D 2000

• Bottling capacity1 L + 1 D 6000

• Market capacity1 L 4000

Page 28: QM B Linear Programming

An aside for SUMPRODUCT function• 2 groups of cells

– Both in a row or both in a columns– Wish to multiply the corresponding entries

then sum the products

=sumproduct(a2:c2, a3:c3)

= 2*5 + 3*6 + 4*7

Page 29: QM B Linear Programming

Think-pair-share: SUMPRODUCT function

=SUMPRODUCT(B6:C6,B10:C10)

= 2*2 + 1*4 = 8

Page 30: QM B Linear Programming

To solve an LP using Excel Solver

• Setup the spreadsheet– TYPE data in one place (go to Excel)

– CREATE Cells for decisions variables

– ENTER formulas to calculate LHS of constraints

– ENTER formulas to calculate Objective Function

• Open solver boxTools -> Solver

Page 31: QM B Linear Programming

Excel Solver Dialog Box

Click on cell that calculates objective function

Select Max or Min

Click & drag to select decision variables

Click add to add the constraints

Page 32: QM B Linear Programming

Excel solver – constraints dialog box

Select cell(s) with LHS

Select symbol (, , =)

Select cell(s) with RHS

Remember – Non-negativity constraints

Page 33: QM B Linear Programming

Go to the Options Dialog box

Click options to assume linear model

Page 34: QM B Linear Programming

Last dialog box - options

Check the Assume linear models box

Click

OK

Check the Assume Non-negative box

Page 35: QM B Linear Programming

Now SOLVEClick solve to find optimal solution

Page 36: QM B Linear Programming

Solver found a solution

Click on Answer and Sensitivity

Click

OK

Page 37: QM B Linear Programming

Answer and sensitivity reports


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