Description
This course provides the student with the fundamentals of mathematical decision-making tools as they are used in operations management. Mathematical programming models including linear and integer programming for resource allocation and transportation models are covered. Mathematical forecasting techniques are reviewed. The student is introduced to the basics of simulation. Students need to have access to a recent version of a spreadsheet program which includes these models.
Prerequisites
Materials
Required:- Spreadsheet Modeling and Decision Analysis, Revised 5th ed. Cliff T. Ragsdale, ITP Southwestern
Course Learning Outcomes
Upon successful completion of this course, the student will:
- Understand the major model used in management
- Be able to apply these models to aid in management solutions.
- Understand the limitations of the use of these models.
Course Topics
- Fundamental concepts and methodology for using mathematical modeling to support decision-making in operations management.
The role and use of spreadsheet technology
Introduction to mathematical programming and constrained optiization models.
The basics of building and solving LP models.
Graphical representation of solutions.
- Using spreadsheets to solve LP problems.
Production blending, scheduling and planning examples of using spreadsheets to solve models.
- Sensitivity analysis and the interpretation of model solutions for decision-making purposes.
- Network and transportation models
Warehousing, transportation, and distribution problems and examples.
- Integer and binary variables in LP models
- Casual forecasting: linear bivariate and multivariate techniques
Non-linear models.
- Overview of forecasting and quantitative forecasting techniques.
Time Series forecasting: averaging and exponential smoothing, trend analysis, seasonality.
- Elements of queuing models: customers, servers and waiting lines.
Their use in measuring and analyzing production and inventory facillities.
- Simulation models
Random variables and random number generators
Functions to make decisions
Kinds of simulations: single event, time-oriented simulation models, event-oriented simulations models
- Replicating the simulations
Generating statistics
Generating tables
Optimizing values
- Decision analysis: uncertaingy, risk and probability, decision trees, conditional probabilities, utility theory
Prerequisites by topic
- Statistics and operations
Laboratory topics
Course topics by day
ACCE content
| General Education |
Math & Science |
Business & Mgmt. |
Construction | Construction Science |
|---|
| 0 | 0 | 0 | 0 | 0 |
ABET/EAC content
| Engineering topics |
Design |
General education |
Math/Science | Other |
|---|
| No |
| | |
ABET/TAC content
| Communications |
Math & Science |
HU/SS |
Tech Content | Other |
|---|
| 0 | 0 | 0 | 0 | 0 |
Coordinator
Bruce Thompson, Professor, Program Director, MSEM
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