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Course Criteria
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4.00 Credits
An introduction to nonlinear programming. Models, methods, algorithms, and computer techniques for nonlinear optimization are studied. Students investigate contemporary optimization methods both by implementing these methods and through experimentation with commercial software. Nonmajors wishing to gain practical optimization skills are welcomed in this course. A course project will allow students to explore optimization methods and practical problems directly related to their interests. Prerequisites/Corequisites: Prerequisites: MATH 2010 or ENGR 1100, and CSCI 1100 or permission of instructor. When Offered: Spring term annually . Cross Listed: Cross-listed as DSES 4780. Students cannot obtain credit for both this course and either MATP 6610 or DSES 4780. Credit Hours: 4
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1.00 - 4.00 Credits
Credit Hours: 1 to 4
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1.00 - 4.00 Credits
Credit Hours: 1 to 4
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1.00 - 4.00 Credits
Credit Hours: 1 to 4
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4.00 Credits
Convex sets and functions, optimality conditions in nonlinear programming, Lagrangian duality, quadratic programming; algorithms for nonlinear programming including Newton's method, quasi-Newton methods, conjugate gradient methods, together with proofs of convergence. Prerequisites/Corequisites: Prerequisite: MATH 4200 or equivalent or permission of instructor. When Offered: Fall term annually. Cross Listed: (Cross listed as DSES 6780. Students cannot obtain credit for both this course and DSES 6780.) Credit Hours: 4
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4.00 Credits
An introduction to nonlinear programming. Models, methods, algorithms, and computer techniques for nonlinear optimization are studied. Students investigate contemporary optimization methods both by implementing these methods and through experimentation with commercial software. Nonmajors wishing to gain practical optimization skills are welcomed in this course. A course project will allow students to explore optimization methods and practical problems directly related to their interests. A computer implementation and a research presentation will be required. Students cannot obtain credit for both this course and either DSES 4780 or MATP 6610. When Offered: Spring term annually. Credit Hours: 4
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4.00 Credits
Exact and heuristic methods for solving discrete problems, including the traveling salesman problem, the knapsack problem, packing and covering problems. Algorithm complexity and NP-completeness, cutting plane methods and polyhedral theory, branch and bound, simulated annealing, tabu search, Lagrangian duality. Prerequisites/Corequisites: Prerequisite: MATP 4700 or DSES 4770. When Offered: Spring term odd-numbered years. Cross Listed: Cross-listed as DSES 6760. Students cannot obtain credit for both this course and DSES 6760. Credit Hours: 4
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4.00 Credits
A unified development of linear systems and linear programming, polyhedral theory, the simplex method, interior point methods, decomposition methods for large-scale linear programming problems, the ellipsoid method, column generation algorithms for stochastic programming, and other problems. Prerequisites/Corequisites: Prerequisite: MATP 4700 or DSES 4770. When Offered: Spring term even-numbered years. Cross Listed: Cross-listed as DSES 6770. Students cannot obtain credit for both this course and DSES 6770. Credit Hours: 4
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1.00 - 4.00 Credits
Credit Hours: 1 to 4
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4.00 Credits
Advanced methods and/or applications in optimization. Possible topics include stochastic programming, learning theory, cone programming, optimization of medical treatment, and network flows. Prerequisites/Corequisites: Prerequisites: vary with topics and/or instructor. When Offered: Fall term annually. Credit Hours: 4
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