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Operations Research (OR) is a branch of industrial and systems engineering that deals with a scientific approach to solving problems faced by decision makers. Broadly defined, this field deals with the efficient design and operation of systems, usually seeking to determine an optimal or effective utilization and allocation of scarce resources. The tools of OR lie in the mathematical modeling and analysis of physical or economic systems, and its scope of application arises in varied walks of life, in the areas of business, industry, government, and national defense. As stiffer competition and lower resilience to business shock make companies and industries walk a tight line that separates success from failure, the emphasis of this field on both long-term (strategic) and short-term (tactical) efficiency and cost effectiveness are increasingly promoting its use in widely diverse areas.
The graduate course work and research orientation within the OR option is designed to educate the student in the process of constructing suitable analytical models for problems arising in various applications, using or developing appropriate (computerized) solution techniques for analyzing these models, and translating the results to implementation in practice. Toward this end, a series of courses have been designed that first provide a student with a knowledge of the tools of OR, followed by courses dealing with different areas of application in which such tools are utilized. The methodological courses cover optimization, stochastic systems modeling and analysis, and Monte Carlo simulation methodology. The application-oriented courses include a study of queueing networks, inventory systems, supply-chain systems, logistics, forecasting, quality assurance and reliability engineering, facilities design, sequencing and scheduling, and production planning and control. The OR faculty also operate and maintain a pc-workstation-based computer laboratory to support computational needs in the areas of optimization and simulation.
The graduate course work and research orientation within the OR option is designed to educate the student in the process of constructing suitable analytical models for problems arising in various applications, using or developing appropriate (computerized) solution techniques for analyzing these models, and translating the results to implementation in practice. Toward this end, a series of courses have been designed that first provide a student with a knowledge of the tools of OR, followed by courses dealing with different areas of application in which such tools are utilized. The methodological courses cover optimization, stochastic systems modeling and analysis, and Monte Carlo simulation methodology. The application-oriented courses include a study of queueing networks, inventory systems, supply-chain systems, logistics, forecasting, quality assurance and reliability engineering, facilities design, sequencing and scheduling, and production planning and control. The OR faculty also operate and maintain a pc-workstation-based computer laboratory to support computational needs in the areas of optimization and simulation.
Students pursuing the M.S. degree are strongly encouraged to select the non-thesis option but the thesis curriculum is also available. Under the thesis-based plan, a minimum of 30 credit hours is required including 15 credit hours of required courses, 9 credits of elective course work and 6 credit hours of thesis research. The non-thesis option specifies 15 credit hours of required courses and 15 credit hours of electives.
The required courses for the M.S. degree are given in the following table:
| Course No. | Course Title | Credit Hrs. |
|---|---|---|
| ISE 5405 | Optimization I | 3 |
| ISE 5406 | Optimization II | 3 |
| ISE 5414 | Random Processes | 3 |
| ISE 5424 | Simulation | 3 |
| ISE 5984 | Mathematical Probability & Statistics | 3 |
The thesis-based M.S. program requires 30 credit hours, including 24 course-credit hours (of which 15 are for required courses) and up to 6 thesis hours. Students must select 9 credit hours of elective course work from either the following list of ISE courses:
| Course No. | Course Title | Credit Hrs. |
|---|---|---|
| ISE 4424 | Logistics Engineering | 3 |
| ISE 5204 | Manufacturing Systems Engineering | 3 |
| ISE 5244 | Facilities Planning and Material Handling | 3 |
| ISE 5434 | Econ. Evaluation of Industrial Projects | 3 |
| ISE 5454 | Production Planning and Control | 3 |
| ISE 5464 | Queueing Theory I | 3 |
| ISE 5474 | Statistical Theory of Quality Control | 3 |
| ISE 5484 | Modeling Processes in Operations Research | 3 |
| ISE 6404 | Graph Theory & Network Flows | 3 |
| ISE 6414 | Integer Programming | 3 |
| ISE 6424 | Dynamic Programming | 3 |
| ISE 6434 | Scheduling and Sequence Theory | 3 |
| ISE 6444 | Inventory and Operations Management | 3 |
| ISE 6454 | Adv Topics in Supply Chain & Operations Mgmt | 3 |
| ISE 6464 | Queueing Networks | 3 |
| ISE 6474 | Reliability Theory | 3 |
| ISE 6494 | Advanced Simulation | 3 |
| ISE 6504 | Markov Renewal and Related Processes | 3 |
| ISE 6514 | Advanced Topics in Math Programming | 3 |
| ISE 6524 | Advanced Topics in Engineering Economy | 3 |
Or from the table on the following page or any relevant graduate courses offered by the university subject to the approval of the student’s committee and the option area coordinator.
| Course No. | Course Title | Credit Hrs. |
|---|---|---|
| CS/Math 5485 | Numerical Analysis and Software I | 3 |
| CS/Math 5486 | Numerical Analysis and Software II | 3 |
| MATH 4226 | Elementary Real Analysis II | 3 |
| MATH 5226 | Real Analysis II | 3 |
| MATH 5454 | Graph Theory | 3 |
| MATH 5464 | Combinatorics | 3 |
| MATH 5524 | Matrix Theory | 3 |
| MATH 5545 | Calculus of Variations and Optimal Control Theory I | 3 |
| MATH 5546 | Calculus of Variations and Optimal Control Theory II | 3 |
| STAT 5124 | Linear Models Theory | 3 |
| STAT 5204 | Experimental Design & Analysis I | 3 |
| STAT 5424 | Statistical Decision Theory | 3 |
| STAT 5434 | Markov Chains & Renewal Theory | 3 |
| STAT 5504 | Multivariate Statistical Methods | 3 |
| STAT 5514 | Regression Analysis | 3 |
| STAT 5554 | Variance Components | 3 |
| STAT 5574 | Response Surface Design and Analysis I | 3 |
| STAT 6106 | Measure and Probability | 3 |
| STAT 6424 | Multivariate Statistical Analysis | 3 |
| STAT 6574 | Response Surface Design and Analysis II | 3 |
| STAT 6504 | Experimental Design II | 3 |
| CS 5114 | Theory of Algorithms | 3 |
| Any ISE Department course that is approved for graduate credit | ||
Students selecting the non-thesis option must complete 30 credit hours of coursework including 15 credits of required courses as enumerated in the following table.
| Course No. | Course Title | Credit Hrs. |
|---|---|---|
| ISE 5405 | Optimization I | 3 |
| ISE 5406 | Optimization II | 3 |
| ISE 5414 | Random processes | 3 |
| ISE 5424 | Simulation | 3 |
| ISE 5984 | Mathematical Probability & Statistics | 3 |
Students in the non-thesis option must then complete 15 credits of courses at least 6 credits of which must be selected from the following list.
| Course No. | Course Title | Credit Hrs. |
|---|---|---|
| ISE 4424 | Logistics engineering | 3 |
| ISE 5204 | Manufacturing systems engineering | 3 |
| ISE 5244 | Facilities planning and material handling | 3 |
| ISE 5434 | Econ. evaluation of industrial projects | 3 |
| ISE 5454 | Production planning and control | 3 |
| ISE 5464 | Queueing theory | 3 |
| ISE 5474 | Statistical theory of quality control | 3 |
| ISE 5484 | Modeling processes in OR | 3 |
| ISE 6404 | Graph theory & network flows | 3 |
| ISE 6414 | Integer programming | 3 |
| ISE 6424 | Dynamic programming | 3 |
| ISE 6434 | Scheduling & sequencing theory | 3 |
| ISE 6464 | Inventory Theory | 3 |
| ISE 6454 | Adv Topics in Supply Chain & Operations Mgmt | 3 |
| ISE 6464 | Queueing networks | 3 |
| ISE 6474 | Reliability theory | 3 |
| ISE 6494 | Advanced Simulation | 3 |
| ISE 6504 | Markov renewal & related processes | 3 |
| ISE 6514 | Advanced topics in math programming | 3 |
| ISE 6524 | Advanced topics in engineering economy | 3 |
Non-thesis students may elect up to 9 credit hours of coursework from the following list or any relevant graduate courses offered by the university subject to the approval of the student’s advisor and the option area coordinator.
| Course No. | Course Title | Credit Hrs. |
|---|---|---|
| CS/Math 5485 | Numerical analysis and software I | 3 |
| CS/Math 5486 | Numerical analysis and software II | 3 |
| MATH 4226 | Elementary real analysis II | 3 |
| MATH 5226 | Real analysis II | 3 |
| MATH 5454 | Graph theory | 3 |
| MATH 5464 | Combinatorics | 3 |
| MATH 5524 | Matrix theory | 3 |
| MATH 5545 | Calculus of variations and optimal control theory I | 3 |
| MATH 5546 | Calculus of variations and optimal control theory II | 3 |
| STAT 5124 | Linear models theory | 3 |
| STAT 5204 | Experimental design & analysis I | 3 |
| STAT 5424 | Statistical decision theory | 3 |
| STAT 5434 | Markov chains & renewal theory | 3 |
| STAT 5504 | Multivariate statistical methods | 3 |
| STAT 5514 | Regression analysis | 3 |
| STAT 5554 | Variance components | 3 |
| STAT 5574 | Response surface design and analysis I | 3 |
| STAT 6106 | Measure and probability | 3 |
| STAT 6424 | Multivariate statistical analysis | 3 |
| STAT 6574 | Response surface design and analysis II | 3 |
| STAT 6504 | Experimental design II | 3 |
| CS 5114 | Theory of algorithms | 3 |
| Any ISE Department course that is approved for graduate credit | ||
