wood 492 modelling for decision support lecture 2 introduction to linear programming

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WOOD 492 MODELLING FOR DECISION SUPPORT Lecture 2 Introduction to Linear Programming

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Page 1: WOOD 492 MODELLING FOR DECISION SUPPORT Lecture 2 Introduction to Linear Programming

WOOD 492 MODELLING FOR DECISION SUPPORT

Lecture 2

Introduction to Linear Programming

Page 2: WOOD 492 MODELLING FOR DECISION SUPPORT Lecture 2 Introduction to Linear Programming

Wood 492 - Saba Vahid 2

Last Class

• Introduction to Operations Research

• Examples of OR in forestry

• Introduction to mathematical models– Objective function, decision variables, constraints

Sept 7, 2012

Page 3: WOOD 492 MODELLING FOR DECISION SUPPORT Lecture 2 Introduction to Linear Programming

Wood 492 - Saba Vahid 3

Example: Custom Cabinets company

• Use excess capacity for 2 new products: Pine desks & Alder hutches

• Has three departments that are partially committed to producing existing products

• Wants to determine how many units of each new product can be produced each week by using the excess capacity of departments to generate the highest profits

Sept 7, 2012

Department Capacity per unit Available capacity per week

Pine desk Alder hutch

Solid wood 0.25 0 12

Panel 0 0.2 5

Finishing 0.25 0.5 18

Profit per unit $40 $50

Objective

Decision variableConstraints

Page 4: WOOD 492 MODELLING FOR DECISION SUPPORT Lecture 2 Introduction to Linear Programming

Wood 492 - Saba Vahid 4

Maximize: x1 = number of desks/week

40 x1 + 50 x2 x2= number of hutches/week

Formulating the Linear Program (LP)

• What do you want to maximize or minimize? Profits

• What are the constraints? Available capacity

Subject to:

0.25x1 <= 12 (Solid Wood Capacity)

0.20x2 <= 5 (Panel Capacity)

0.25x1 + 0.50x2 <= 18 (Finishing Capacity)

x1 >= 0

x2 >= 0

Sept 7, 2012

Linear

Page 5: WOOD 492 MODELLING FOR DECISION SUPPORT Lecture 2 Introduction to Linear Programming

Note that because of the inequalities there are many feasible solutions. You have to find the best one.

Maximize:

$40x1 + $50x2

Subject to:

0.25x1 <= 12 (Solid Wood Capacity)

0.20x2 <= 5 (Panel Capacity)

0.25x1 + 0.50x2 <= 18 (Finishing Capacity)

x1 >= 0

x2 >= 0

Solving the LP by trial and error

Sept 7, 2012 5Wood 492 - Saba Vahid

Try x1 = 10, x2 = 5Z=$650All constraints are satisfied

Custom Cabinet LP1

Page 6: WOOD 492 MODELLING FOR DECISION SUPPORT Lecture 2 Introduction to Linear Programming

Matrix format for LP

Sept 7, 2012 6Wood 492 - Saba Vahid

# Desks # Hutches

Answer x1 x2

Objective (profits) $40.00 $50.00 sign RHS

Solid Wood 0.25 0 <= 12

Panel 0 0.2 <= 5

Finishing 0.25 0.5 <= 18

non-negative 1 0  >= 0

non-negative   1 >= 0

Custom Cabinet LP2

Page 7: WOOD 492 MODELLING FOR DECISION SUPPORT Lecture 2 Introduction to Linear Programming

Wood 492 - Saba Vahid 7

0

10

20

30

40

50

60

70

80

0 20 40 60 80

hu

tch

es p

rod

uce

d (

x2)

desks produced (x1)

wood

panel

f inish

Prof it

Sept 7, 2012

Feasible Region

Custom Cabinet LP2

Page 8: WOOD 492 MODELLING FOR DECISION SUPPORT Lecture 2 Introduction to Linear Programming

Wood 492 - Saba Vahid 8Sept 7, 2012

0

10

20

30

40

50

60

70

80

0 20 40 60 80

hu

tch

es p

rod

uce

d (

x2)

desks produced (x1)

wood

panel

f inish

Prof it

Custom Cabinet LP2

Z=1000

Z=2000

x1 =480.25*48 + 0.5* x2 =18x2 =12

Page 9: WOOD 492 MODELLING FOR DECISION SUPPORT Lecture 2 Introduction to Linear Programming

Wood 492 - Saba Vahid 9

Example: Whitt Window Company (prob. 3.1-7)

• Has three employees• Makes two types of windows: wood-framed and aluminium-framed• Profits per frame: $180 for wood-framed, $90 for aluminum-framed• Dough makes a maximum of 6 wood frames per day• Linda makes a maximum of 4 aluminium frames per day• Bob forms and cuts a maximum of 48 ft2 of glass per day• Each wood-framed window uses 6 ft2 glass• Each aluminum-framed window uses 8 ft2 glass• How many windows per day to make in order to maximize profits?

Sept 7, 2012

Objective

Decision variables

Constraints

Whitt Windows LP

Page 10: WOOD 492 MODELLING FOR DECISION SUPPORT Lecture 2 Introduction to Linear Programming

Wood 492 - Saba Vahid 10

Next Week

• Solving an LP with Excel Solver• Simplex Algorithm

Sept 7, 2012