Solution manual for Introduction to Management Science
Quantitative Approaches to Decision Making 14th Edition
Anderson 1111823618 9781111823610
Full link download:
Test Bank:
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introduction-to-management-science-quantitative-
approaches-to-decision-making-14th-edition-
anderson-1111823618-9781111823610/
Solution Manual:
https://testbankpack.com/p/solution-manual-for-
introduction-to-management-science-quantitative-
approaches-to-decision-making-14th-edition-anderson-
1111823618-9781111823610/
Chapter 2
An Introduction to Linear Programming
Learning Objectives
1. Obtain an overview of the kinds of problems linear programming has been used to solve.
2. Learn how to develop linear programming models for simple problems.
3. Be able to identify the special features of a model that make it a linear programming model.
4. Learn how to solve two variable linear programming models by the graphical solution procedure.
5. Understand the importance of extreme points in obtaining the optimal solution.
6. Know the use and interpretation of slack and surplus variables.
7. Be able to interpret the computer solution of a linear programming problem.
8. Understand how alternative optimal solutions, infeasibility and unboundedness can
occur in linear programming problems.
9. Understand the following terms:
problem formulation feasible region
constraint function slack variable
objective function standard form
solution redundant constraint
optimal solution extreme point
nonnegativity constraints surplus variable
mathematical model alternative optimal solutions
linear program infeasibility
linear functions unbounded
,feasible solution
2-1
,Chapter 2
Solutions:
1. a, b, and e, are acceptable linear programming
relationships. c is not acceptable because of 2B2
d is not acceptable because of 3
A f is not acceptable because of 1AB
c, d, and f could not be found in a linear programming model because they have the
above nonlinear terms.
2. a.
B
8
4
A
0 4 8
b.
B
8
4
A
0 4 8
c.
B
8 Points on line
are only feasible
points
4
A
0 4 8
2-2
2-2
, Chapter 2 An Introduction to Linear Programming
3. a.
B
(0,9)
A
0 (6,0)
b.
B
(0,60)
A
0 (40,0)
c.
B
Points
on line are only
feasible solutions
(0,20)
A
0 (40,0)
4. a.
B
(20,0) A
(0,-15)
2-3
2-3
Quantitative Approaches to Decision Making 14th Edition
Anderson 1111823618 9781111823610
Full link download:
Test Bank:
https://testbankpack.com/p/test-bank-for-
introduction-to-management-science-quantitative-
approaches-to-decision-making-14th-edition-
anderson-1111823618-9781111823610/
Solution Manual:
https://testbankpack.com/p/solution-manual-for-
introduction-to-management-science-quantitative-
approaches-to-decision-making-14th-edition-anderson-
1111823618-9781111823610/
Chapter 2
An Introduction to Linear Programming
Learning Objectives
1. Obtain an overview of the kinds of problems linear programming has been used to solve.
2. Learn how to develop linear programming models for simple problems.
3. Be able to identify the special features of a model that make it a linear programming model.
4. Learn how to solve two variable linear programming models by the graphical solution procedure.
5. Understand the importance of extreme points in obtaining the optimal solution.
6. Know the use and interpretation of slack and surplus variables.
7. Be able to interpret the computer solution of a linear programming problem.
8. Understand how alternative optimal solutions, infeasibility and unboundedness can
occur in linear programming problems.
9. Understand the following terms:
problem formulation feasible region
constraint function slack variable
objective function standard form
solution redundant constraint
optimal solution extreme point
nonnegativity constraints surplus variable
mathematical model alternative optimal solutions
linear program infeasibility
linear functions unbounded
,feasible solution
2-1
,Chapter 2
Solutions:
1. a, b, and e, are acceptable linear programming
relationships. c is not acceptable because of 2B2
d is not acceptable because of 3
A f is not acceptable because of 1AB
c, d, and f could not be found in a linear programming model because they have the
above nonlinear terms.
2. a.
B
8
4
A
0 4 8
b.
B
8
4
A
0 4 8
c.
B
8 Points on line
are only feasible
points
4
A
0 4 8
2-2
2-2
, Chapter 2 An Introduction to Linear Programming
3. a.
B
(0,9)
A
0 (6,0)
b.
B
(0,60)
A
0 (40,0)
c.
B
Points
on line are only
feasible solutions
(0,20)
A
0 (40,0)
4. a.
B
(20,0) A
(0,-15)
2-3
2-3
