IE 525  System Synthesis and Design
Brief Course Description
Production and other systems can be modeled as networks of transmission links
interconnecting sources, processing points, and destinations. Additionally, many problems, such
as scheduling, machine replacement, distribution systems, and even roller coaster design, can be formulated as
network problems. Such a formulation can vastly reduce the time required to find an answer. For example, one recent graduate student reduced the solution time for one problem from 10^{54}
years (much longer than the estimated life of the Universe) to about half an hour.
IE 525 focuses on modeling situations as networks, using computers to find results, then interpreting those results. In addition, students will gain skill in choosing appropriate models and algorithms in a variety of situations.
Course Objectives
Students successfully completing IE 525 will:
 develop skill in observing and representing the structure, as well as the data, in a variety of situations,
 develop knowledge and skill in exploiting the special structure of these situations leading to more
efficient, or even feasible, methods of solution, and
 demonstrate an ability to use a hand computations to solve small problems and a computer to solve
moderately large ones.
Main Topics
The course material is organized into four units:
 Fundamentals: An overview of the course approach, as well as notation and conventions that will be
used throughout the course. This unit also includes an introduction to the computer tools you will use.
 Shortest Path Problems: Here, the main task is to find a shortest or cheapest route through a
network.
 Maximum Flow Problems are ones in which the main problem is to find out the greatest amount
of material that can be moved through the network from one specific node to another.
 Minimum Cost Flow Problems are ones in which the main task is to move a specified amount of
material through the network at the lowest possible cost.
Within each unit, the following topics will be addressed.
 Modeling: the task of abstracting key elements of the situation to form an analytical model
 Representation: the problem of depicting the elements of the model in graphical, mathematical, and
computerusable forms.
 Algorithms: which are the stepbystep processes that lead to a solution.
 Transformations: which allow us to use the method for one problem to solve a larger class of problems.
 Basic Problem Types: which include shortest path, maximum flow, lowestcost flow, and minimal
spanning trees. We will examine the nature of realworld problems of these types as well as algorithms
that may solve them.
 Efficiency: which arises as an issue in the timely solution of practical problems. This includes the
problem of collecting and processing data as well as computer time to solve it.
 Computer resources: which includes the tradeoff of using generalpurpose vs. specialpurpose
software.
 Interpretation of algorithm results or computer output in the context of the original problem.
 Sensitivity of solutions to inaccuracies or changes in the data.
Details:
Instructor: 
John Mullen,
Tel: (575) 6462958,
email: jomullen@nmsu.edu 
Texts: 
Network Flows: Theory, Algorithms, and Applications, by R. K. Ahuja, Thomas L. Magnanti, and
James B. Orlin. Prentice Hall, 1993, ISBN 013617549X. We will use parts of chapters 1 through 9 and 11
through 13. Additional resources are available through the WebCT site. 
Computer: 
 WebCT
Site: https://salsa.nmsu.edu/
 MatLab
 LINDO and LINGO

Note: Your primary computer tool in this course will be MatLab. In addition, you will do a
few problems in LINDO and LINGO. All of these are are commercial problemsolving tools which are available in the
IE computer lab. If you want to install these programs on your own computer, moderatelypriced student
versions are available. See the WebCT site for details. You can also download free evaluation copies of LINDO
and LINGO which are not as capable as the student version, but adequate for IE 525.
Revision Date: November 13, 2008 by jpm.