Undergraduate Courses
IE 1055/2025
Course Outline:
This course provides an introduction to facility layout and location.
The course topics tentatively include: an overview of why facility
layout is important, activity relationships, space and personnel
requirements, manufacturing flow patterns, layout procedure types
- both construction and improvement algorithms, manual and computerized
layout techniques, modular facilities (QAP), single and multiple
facility location, and material handling system design. Some of
these topics may be deleted or added depending upon time constraints.
We will also discuss the use of software packages for
constructing facility layouts.
Prerequisites: IE 1021
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IE 1056/2083
Course Outline:
This course provides an introduction to production planning and
inventory control. The course topics tentatively include:
a history of manufacturing in America, inventory control,
material requirements planning (MRP), MRP II, ERP, JIT,
variability - and its effect on operations, push and pull systems,
the human element in operations, shop floor control,
production scheduling, aggregate planning,
supply chain management, and capacity management.
Some of these topics may be deleted or added
depending upon time constraints.
Prerequisites: IE 1021, IE 1081 or IE 2001
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IE 1081
Course Outline:
This course provides an introduction to general operations research
(OR) methodology, with primary emphasis on linear programming
(LP). The course topics tentatively include: a brief history and
philosophy of OR; modeling and formulation of linear programs;
graphical solution methods for linear programs; the simplex method;
sensitivity analysis; transportation and assignment problems;
network models; and integer programming. Some of these topics
may be deleted or added depending upon time constraints. We will
also discuss the use of software packages, LINDO and/or STORM,
for solving linear programs.
Prerequisites: Math 0250, IE 1021
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ENGR 0020
Course Description:
This course is designed for students majoring in engineering.
Topics include: data analysis, probability, random variables,
discrete and continuous probability distributions, estimation,
hypothesis testing, correlation, linear regression, and statistical
process control.
Course Objectives:
- To acquaint the students with the fundamental concepts of
probability and statistics.
- To develop an understanding of the role of statistics in
engineering.
- To provide an understanding of the processes by which real-life
statistical problems are analyzed.
- To familiarize students with computer-based statistical analysis
through the Statistix software package.
Prerequisites:
None
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Graduate Courses
IE 3082
Course Outline:
Scheduling machines, operations, and personnel continues to be
an important consideration for many companies in both manufacturing
and service settings. In this course we will examine solution
methodologies for a wide range of different scheduling problems.
A general outline of the topics to be covered is provided below.
The course material will include recent papers from the literature.
There will also be a term project that will permit students to
both apply their understanding of existing solution methodologies
and to explore new solution methodologies.
Topics Covered:
- Introduction
- Single-machine sequencing with independent jobs
- Optimization methods for the single-machine problem
- Heuristic methods for the single-machine problem
- Earliness and tardiness penalties
- Extensions of the basic model
- Parallel-machine models
- Flow shop scheduling
- Lot streaming procedures for the flow shop
- The job shop problem
- Scheduling groups of jobs
- Simulation models for the dynamic job shop
- Stochastic scheduling models
Prerequisites:
Students taking this course should have a general knowledge of
optimization theory and linear programming similar to that found
in IE 2001.
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IE 3087
Course Goals:
- Develop an awareness of network flow formulations for a variety
of real life problems.
- Understand the use of network flow algorithms to solve such
problems.
- Develop the ability to program network flow problems.
- Develop the ability to understand and implement research papers
related to network analysis.
Course Outline:
- Network Formulations of Some Problems
- Combinatorial Optimization
- Graph Theory Concepts
- Linear Programming and Network Flows
- Shortest Path Algorithms
- Maximum Flow Algorithms
- Minimum Cost Flow Problem
- Minimum Spanning Tree Algorithms
- Convex Cost Flow Problems
- Generalized Network Flows
- Traveling Salesman Problem
Prerequisites:
IE 2001
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