2 linear programming

© 2008 Prentice-Hall, Inc.
Chapter 7
To accompany
Quantitative Analysis for Management, Tenth Edition,
by Render, Stair, and Hanna
Power Point slides created by Jeff Heyl
Linear Programming Models:
Graphical and Computer
Methods
© 2009 Prentice-Hall, Inc.

© 2009 Prentice-Hall, Inc. 7 – 2
Introduction
 Many management decisions involve trying to
make the most effective use of limited resources
 Machinery, labor, money, time, warehouse space, raw
materials
 Linear programming (LP) is a widely used
mathematical modeling technique designed to
help managers in planning and decision making
relative to resource allocation
 Belongs to the broader field of mathematical
programming
 In this sense, programming refers to modeling and
solving a problem mathematically

Requirements of a Linear
Programming Problem
 LP has been applied in many areas over the past
50 years
 All LP problems have 4 properties in common
1. All problems seek to maximize or minimize some
quantity (the objective function)
2. The presence of restrictions or constraints that limit the
degree to which we can pursue our objective
3. There must be alternative courses of action to choose
from
4. The objective and constraints in problems must be
expressed in terms of linear equations or inequalities

LP Properties and Assumptions
PROPERTIES OF LINEAR PROGRAMS
1. One objective function
2. One or more constraints
3. Alternative courses of action
4. Objective function and constraints are linear
ASSUMPTIONS OF LP
1. Certainty
2. Proportionality
3. Additivity
4. Divisibility
5. Nonnegative variables
Table 7.1

Basic Assumptions of LP
 We assume conditions of certainty exist and
numbers in the objective and constraints are
known with certainty and do not change during
the period being studied
 We assume proportionality exists in the objective
and constraints
 We assume additivity in that the total of all
activities equals the sum of the individual
activities
 We assume divisibility in that solutions need not
be whole numbers
 All answers or variables are nonnegative

Formulating LP Problems
 Formulating a linear program involves developing
a mathematical model to represent the managerial
problem
 The steps in formulating a linear program are
1. Completely understand the managerial
problem being faced
2. Identify the objective and constraints
3. Define the decision variables
4. Use the decision variables to write
mathematical expressions for the objective
function and the constraints

Formulating LP Problems
 One of the most common LP applications is the
product mix problem
 Two or more products are produced using
limited resources such as personnel, machines,
and raw materials
 The profit that the firm seeks to maximize is
based on the profit contribution per unit of each
product
 The company would like to determine how
many units of each product it should produce
so as to maximize overall profit given its limited
resources

Flair Furniture Company
 The Flair Furniture Company produces
inexpensive tables and chairs
 Processes are similar in that both require a certain
amount of hours of carpentry work and in the
painting and varnishing department
 Each table takes 4 hours of carpentry and 2 hours
of painting and varnishing
 Each chair requires 3 of carpentry and 1 hour of
painting and varnishing
 There are 240 hours of carpentry time available
and 100 hours of painting and varnishing
 Each table yields a profit of $70 and each chair a
profit of $50

 The company wants to determine the best
combination of tables and chairs to produce to
reach the maximum profit
HOURS REQUIRED TO
PRODUCE 1 UNIT
DEPARTMENT
(T)
TABLES
(C)
CHAIRS
AVAILABLE HOURS
THIS WEEK
Carpentry 4 3 240
Painting and varnishing 2 1 100
Profit per unit $70 $50
Table 7.2

 The objective is to
Maximize profit
 The constraints are
1. The hours of carpentry time used cannot
exceed 240 hours per week
2. The hours of painting and varnishing time
used cannot exceed 100 hours per week
 The decision variables representing the actual
decisions we will make are
T = number of tables to be produced per week
C = number of chairs to be produced per week

 We create the LP objective function in terms of T
and C
Maximize profit = $70T + $50C
 Develop mathematical relationships for the two
constraints
 For carpentry, total time used is
(4 hours per table)(Number of tables produced)
+ (3 hours per chair)(Number of chairs produced)
 We know that
Carpentry time used ≤ Carpentry time available
4T + 3C ≤ 240 (hours of carpentry time)

 Similarly
Painting and varnishing time used
≤ Painting and varnishing time available
2 T + 1C ≤ 100 (hours of painting and varnishing time)
This means that each table produced
requires two hours of painting and
varnishing time
 Both of these constraints restrict production
capacity and affect total profit

 The values for T and C must be nonnegative
T ≥ 0 (number of tables produced is greater
than or equal to 0)
C ≥ 0 (number of chairs produced is greater
than or equal to 0)
 The complete problem stated mathematically
Maximize profit = $70T + $50C
subject to
4T + 3C ≤ 240 (carpentry constraint)
2T + 1C ≤ 100 (painting and varnishing constraint)
T, C ≥ 0 (nonnegativity constraint)

Cycle Trends is introducing two new lightweight bicycle
frames, the Deluxe and the Professional, to be made from
aluminum and steel alloys. The anticipated unit profits are $10
for the Deluxe and $15 for the Professional.
The number of pounds of each alloy needed per frame is
summarized on the table. A supplier delivers 100 pounds of the
aluminum alloy and 80 pounds of the steel alloy weekly. How
many Deluxe and Professional frames should Cycle Trends
produce each week?
Pounds of each alloy needed per frame
1- Example: LP Formulation
Aluminum Alloy Steel Alloy
Deluxe 2 3
Professional 4 2

Montana Wood Products manufacturers two-
high quality products, tables and chairs. Its profit is
$15 per chair and $21 per table. Weekly production is
constrained by available labor and wood. Each chair
requires 4 labor hours and 8 board feet of wood while
each table requires 3 labor hours and 12 board feet of
wood. Available wood is 2400 board feet and available
labor is 920 hours. Management also requires at least
40 tables and at least 4 chairs be produced for every
table produced. To maximize profits, how many chairs
and tables should be produced?

The Sureset Concrete Company produces
concrete. Two ingredients in concrete are sand (costs
$6 per ton) and gravel (costs $8 per ton). Sand and
gravel together must make up exactly 75% of the
weight of the concrete. Also, no more than 40% of the
concrete can be sand and at least 30% of the concrete
be gravel. Each day 2000 tons of concrete are
produced. To minimize costs, how many tons of gravel
and sand should be purchased each day?

A company produces two products that are processed on two
assembly lines. Assembly line 1 has 100 available hours, and
assembly line 2 has 42 available hours. Each product requires
10 hours of processing time on line 1, while on line 2 product
1 requires 7 hours and product 2 requires 3 hours. The profit
for product 1 is $6 per unit, and the profit for product 2 is $4
per unit.
Formulate a linear programming model for this problem.

A California grower has a 50-acre farm on which to plant
strawberries and tomatoes. The grower has available 300 hours of
labor per week and 800 tons of fertilizer, and he has contracted for
shipping space for a maximum of 26 acres' worth of strawberries
and 37 acres' worth of tomatoes. An acre of strawberries requires
10 hours of labor and 8 tons of fertilizer, whereas an acre of
tomatoes requires 3 hours of labor and 20 tons of fertilizer. The
profit from an acre of strawberries is $400, and the profit from an
acre of tomatoes is $300. The farmer wants to know the number of
acres of strawberries and tomatoes to plant to maximize profit.
Formulate a linear programming model for this problem.

2 linear programming

More Related Content

What's hot (20)

Similar to 2 linear programming (20)

More from Dronak Sahu (20)

Recently uploaded (20)

2 linear programming