Minor in Operations Research
Program Learning Outcomes for the Minor in Operations Research
Upon completing the minor in Operations Research, students will be able to:
- Formulate appropriate mathematical programs and stochastic processes that model real-world situations.
- Calibrate models with appropriate real-world data, using statistical and data science tools.
- Use commercial and open-source software to solve operations research models.
Requirements for the Minor in Operations Research
Students pursuing the minor in Operations Research must complete:
- A minimum of 6 courses (19-20 credit hours, depending on course selection) to satisfy minor requirements.
- A minimum of 6 courses (19-20 credit hours, depending on course selection) taken at the 300-level or above.
- A maximum of 2 courses (6 credit hours) from study abroad or transfer credit. For additional departmental guidelines regarding transfer credit, see the Policies tab.
The courses listed below satisfy the requirements for this minor. In certain instances, courses not on this official list may be substituted upon approval of the minor’s academic advisor or, where applicable, the Program Director. (Course substitutions must be formally applied and entered into Degree Works by the minor's Official Certifier). Students and their academic advisors should identify and clearly document the courses to be taken.
Summary
| Code | Title | Credit Hours |
|---|---|---|
| Total Credit Hours Required for the Minor in Operations Research | 19-20 | |
Minor Requirements
| Code | Title | Credit Hours |
|---|---|---|
| Core Requirements | ||
| CMOR 350 | STOCHASTIC MODELS | 3 |
| CMOR 360 | INTRODUCTION TO OPERATIONS RESEARCH AND OPTIMIZATION | 3 |
| CMOR 461 | LOGISTICS AND SUPPLY CHAIN MANAGEMENT | 3 |
| or CMOR 462 | OPTIMIZATION METHODS IN FINANCE | |
| STAT 315 / DSCI 301 | PROBABILITY AND STATISTICS FOR DATA SCIENCE | 4 |
| Elective Requirements | ||
| Select 2 elective courses (see course list below) | 6-7 | |
| Total Credit Hours | 19-20 | |
Course List to Satisfy Requirements
To fulfill Elective Requirements, students must complete a total of 2 courses (6-7 credit hours, depending on course selection) from the following department approved electives.
| Code | Title | Credit Hours |
|---|---|---|
| CMOR 404 | GRAPH THEORY | 3 |
| CMOR 442 | LARGE-SCALE OPTIMIZATION | 3 |
| CMOR 446 | GRAPH ALGORITHMS | 3 |
| CMOR 451 | SIMULATION MODELING AND ANALYSIS | 3 |
| CMOR 452 | SERVICE SYSTEMS ANALYTICS | 3 |
| CMOR 455 | STOCHASTIC CONTROL AND APPLICATIONS | 3 |
| CMOR 461 | LOGISTICS AND SUPPLY CHAIN MANAGEMENT | 3 |
| or CMOR 462 | OPTIMIZATION METHODS IN FINANCE | |
| CMOR 463 | OPERATIONS RESEARCH IN HEALTHCARE | 3 |
| CMOR 464 | MANUFACTURING PROCESSES AND SYSTEMS | 3 |
| CMOR 531 | CONVEX OPTIMIZATION | 3 |
| CMOR 533 | NUMERICAL OPTIMIZATION | 3 |
| CMOR 543 | COMBINATORIAL OPTIMIZATION | 3 |
| CMOR 544 | STOCHASTIC OPTIMIZATION | 3 |
| COMP 341 | PRACTICAL MACHINE LEARNING FOR REAL WORLD APPLICATIONS | 3 |
| or COMP 441 | LARGE-SCALE MACHINE LEARNING | |
| or DSCI 303 | MACHINE LEARNING FOR DATA SCIENCE | |
| or ELEC 378 | MACHINE LEARNING: CONCEPTS AND TECHNIQUES | |
| or ELEC 478 | INTRODUCTION TO MACHINE LEARNING | |
| or INDE 577 | DATA SCIENCE AND MACHINE LEARNING | |
| or STAT 413 | INTRODUCTION TO STATISTICAL MACHINE LEARNING | |
| ECON 343 | CORPORATE FINANCE | 3 |
| ECON 437 / ENST 437 | ENERGY ECONOMICS | 3 |
| ECON 443 | FINANCIAL ECONOMICS | 3 |
| ECON 445 | MANAGERIAL ECONOMICS | 3 |
| ECON 449 | PRINCIPLES OF FINANCIAL ENGINEERING | 3 |
| ECON 456 | TOPICS IN BUSINESS ECONOMICS: FINANCIAL MARKET AND INVESTMENTS | 3 |
| ECON 470 | MARKET DESIGN | 3 |
| ECON 481 | HEALTH ECONOMICS | 3 |
| ELEC 475 | LEARNING FROM SENSOR DATA | 3 |
| ELEC 533 / CMOR 553 / STAT 583 | INTRODUCTION TO RANDOM PROCESSES AND APPLICATIONS | 3 |
| INDE 597 | TOPICS IN INDUSTRIAL ENGINEERNG | 3 |
| STAT 313 / CEVE 313 | UNCERTAINTY AND RISK IN URBAN INFRASTRUCTURES | 3 |
| STAT 410 | LINEAR REGRESSION | 4 |
| STAT 418 | PROBABILITY | 3 |
| STAT 419 | STATISTICAL INFERENCE | 3 |
| STAT 421 | APPLIED TIME SERIES AND FORECASTING | 3 |
| STAT 449 | QUANTITATIVE FINANCIAL RISK MANAGEMENT | 3 |
| STAT 482 | QUANTITATIVE FINANCIAL ANALYTICS | 3 |
| STAT 486 | MARKET MODELS | 3 |
| STAT 581 / CMOR 552 | MATHEMATICAL PROBABILITY I | 3 |
| STAT 582 | MATHEMATICAL PROBABILITY II | 3 |
Policies for the Minor in Operations Research
Program Restrictions and Exclusions
Students pursuing the minor in Operations Research should be aware of the following program restrictions:
- As noted in Majors, Minors, and Certificates, students may not major and minor in the same subject.
- Students pursuing the major in Computational and Applied Mathematics may not additionally declare the minor in Operations Research.
- Students pursuing the minor in Computational and Applied Mathematics may not additionally declare the minor in Operations Research.
Transfer Credit
For Rice University’s policy regarding transfer credit, see Transfer Credit. Some departments and programs have additional restrictions on transfer credit. Requests for transfer credit must be approved for Rice equivalency by the designated transfer credit advisor for the appropriate academic department offering the Rice equivalent course (corresponding to the subject code of the course content). The Office of Academic Advising maintains the university’s official list of transfer credit advisors on their website: https://oaa.rice.edu. Students are encouraged to meet with the applicable transfer credit advisor as well as their academic program director when considering transfer credit possibilities.
Departmental Transfer Credit Guidelines
Students pursuing the minor in Operations Research should be aware of the following departmental transfer credit guideline:
- No more than 2 courses (6 credit hours) of transfer credit from U.S. or international universities of similar standing as Rice may apply towards the minor.
Additional Information
For additional information, please see the Computational Applied Mathematics and Operations Research website: https://cmor.rice.edu/.
Opportunities for the Minor in Operations Research
Academic Honors
The university recognizes academic excellence achieved over an undergraduate’s academic history at Rice. For information on university honors, please see Latin Honors (summa cum laude, magna cum laude, and cum laude) and Distinction in Research and Creative Work. Some departments have department-specific Honors awards or designations.
Additional Information
For additional information, please visit the Computational Applied Mathematics and Operations Research website: https://cmor.rice.edu/.