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MGMT 1050 Quiz: stats book summary notes pt3
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5 Pages
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Fall 2014

Department
Management
Course Code
MGMT 1050
Professor
Olga Kraminer
Study Guide
Quiz

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The Q.M. in Action, Tea Production and Distribution at Duncan Industries
Limited, illustrates the diversity of problem situations in which linear
programming can be applied and the importance of sensitivity analysis. In the
next chapter we will see many more applications of linear programming.
Chapter 9 Linear Programming Applications in Marketing, Finance, and
Operations Management
a broad range of applications that demonstrate how to use linear programming
to assist in the decision-making process. We formulated and solved problems
from marketing, finance, and operations management, and interpreted the
computer output.
Many of the illustrations presented in this chapter are scaled-down versions of
actual situations in which linear programming has been applied. In real-world
applications, the problem may not be so concisely stated, the data for the
problem may not be as readily avail- able, and the problem most likely will
involve numerous decision variables and/or constraints. However, a thorough
study of the applications in this chapter is a good place to begin in applying linear
programming to real problems.
Chapter 10 Distribution and Network Models
models related to supply chain problemsspecifically, transportation and
transshipment problemsas well as assignment, shortest-route, and maximal
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flow problems. All of these types of problems belong to the special category of
linear pro- grams called network flow problems. In general, the network model
for these problems consists of nodes representing origins, destinations, and, if
necessary, transshipment points in the network system. Arcs are used to
represent the routes for shipment, travel, or flow be- tween the various nodes.
Transportation problems and transshipment problems are commonly
encountered when dealing with supply chains. The general transportation
problem has m origins and n destinations. Given the supply at each origin, the
demand at each destination, and unit shipping cost between each origin and each
destination, the transportation model determines the optimal amounts to ship
from each origin to each destination. The transshipment problem is
an extension of the transportation problem involving transfer points referred to
as transshipment nodes. In this more general model, we allow arcs between any
pair of nodes in the network.
The assignment problem is a special case of the transportation problem in which
all sup- ply and all demand values are 1. We represent each agent as an origin
node and each task as a destination node. The assignment model determines the
minimum cost or maximum profit assignment of agents to tasks.
The shortest-route problem finds the shortest route or path between two nodes
of a net- work. Distance, time, and cost are often the criteria used for this model.
The shortest-route problem can be expressed as a transshipment problem with
one origin and one destination. By shipping one unit from the origin to the
destination, the solution will determine the shortest route through the network.
The maximal flow problem can be used to allocate flow to the arcs of the network
so that flow through the network system is maximized. Arc capacities determine
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Description
The Q.M. in Action, Tea Production and Distribution at Duncan Industries Limited, illustrates the diversity of problem situations in which linear programming can be applied and the importance of sensitivity analysis. In the next chapter we will see many more applications of linear programming. Chapter 9 Linear Programming Applications in Marketing, Finance, and Operations Management a broad range of applications that demonstrate how to use linear programming to assist in the decision-making process. We formulated and solved problems from marketing, finance, and operations management, and interpreted the computer output. Many of the illustrations presented in this chapter are scaled-down versions of actual situations in which linear programming has been applied. In real-world applications, the problem may not be so concisely stated, the data for the problem may not be as readily avail- able, and the problem most likely will involve numerous decision variables and/or constraints. However, a thorough study of the applications in this chapter is a good place to begin in applying linear programming to real problems. Chapter 10 Distribution and Network Models models related to supply chain problems—specifically, transportation and transshipment problems—as well as assignment, shortest-route, and maximal The Q.M. in Action, Tea Production and Distribution at Duncan Industries Limited, illustrates the diversity of problem situations in which linear programming can be applied and the importance of sensitivity analysis. In the next chapter we will see many more applications of linear programming. Chapter 9 Linear Programming Applications in Marketing, Finance, and Operations Management a broad range of applications that demonstrate how to use linear programming to assist in the decision-making process. We formulated and solved problems from marketing, finance, and operations management, and interpreted the computer output. Many of the illustrations presented in this chapter are scaled-down versions of actual situations in which linear programming has been applied. In real-world applications, the problem may not be so concisely stated, the data for the problem may not be as readily avail- able, and the problem most likely will involve numerous decision variables and/or constraints. However, a thorough study of the applications in this chapter is a good place to begin in applying linear programming to real problems. Chapter 10 Distribution and Network Models models related to supply chain problems—specifically, transportation and transshipment problems—as well as assignment, shortest-route, and maximal
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