| Instructor: | David Rader |
| Time: | Thursday Evening 5:30 - 9 PM at RHIT |
| Prerequisite: | Senior or graduate standing |
| Credits: | 4 |
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(1) How do companies decide how much of a product to make and where
to ship it?
(2) How companies deal with long-range planning of inventory levels
or manpower?
(3) How probability and simulation play an important role in the design
of various products and systems?
This course deals with formulating these and other problems as mathematical models. Such models have recently been used in all levels of business and industry because of spreadsheet packages such as Microsoft Excel, which has macros designed to solve mathematical problems.
The mathematical models we will be studying include linear programs, integer programs, and some network models such as maximum flow models and minimum cost network flow models. Also, we will look at inventory models (when to purchase inventory, and how much to get), simulation, and perhaps queueing models. In addition, we will look at how these and other models are currently being used to solve many real-world problems in business and industry.
This is an applied math course for computer scientists, engineers ( especially
those with managerial aspirations) and, of course, mathematicians. It
is also a management course for the Engineering Management graduate program.
It assumes a technical background and (some) experience with Excel.
Employment is projected to grow much faster than average. Individuals with a master's or Ph.D. degree in operations research or management science should have excellent job opportunities; some entry-level positions are available to those with a bachelor’s degree.
Employment change. Employment of operations research analysts is expected to grow 22 percent over the 2008-18 period, much faster than the average for all occupations. As technology advances and companies further emphasize efficiency, demand for operations research analysis should continue to grow. Technological advancements have extended the availability of data access and storage, making information more readily available. Advancements in computing capabilities and analytical software have made it cheaper and faster for analysts to solve problems. As problem solving becomes cheaper and faster with technological advances, more firms will have the ability to employ or consult with analysts.
Additionally, organizations increasingly will be faced with the pressure of growing domestic and international competition and must work to maximize organizational efficiency. As a result, businesses increasingly will rely on operations research analysts to optimize profits by improving productivity and reducing costs. As new technologies are introduced into the marketplace, operations research analysts will be needed to determine how to best use those new technologies.