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OR 750: Advanced Topics in Operations Research
3.00 Credits
George Mason University
Credits: 3 Special topics, applications, or recent developments in operations research. Contents vary and may include topics in optimization, stochastic methods, or decision support that are not covered in the standard OR curriculum. Prerequisites OR 541 or 542, and 600-level course that varies with content of course. Notes May be repeated for credit when topics are distinctly different. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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OR 750 - Advanced Topics in Operations Research
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OR 751: Advanced Topics in Operations Research for Planning,Scheduling,and Network Design
3.00 Credits
George Mason University
Credits: 3 Introduces network and combinatorial optimization problems in logistics, computer science, electrical engineering, and systems engineering. Solution techniques for various classes of such problems are developed. Topics include scheduling algorithms, capital budgeting, minimal cost network flow, optimal routings, and generalized networks. Scheduling algorithms, network reliability, stochastic networks, and combinatorially based network problems are discussed. Prerequisites OR 642, 643, or 690. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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OR 751 - Advanced Topics in Operations Research for Planning,Scheduling,and Network Design
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OR 763: Research Methods in Systems Engineering and Information Technology
3.00 Credits
George Mason University
Credits: 3 Cross-Listed with IT 763/SYST 763 Examines alternative paradigms of scientific research and their applicability to research in information technology. Topics include fundamental elements of scientific investigation, basic principles of experimental design and statistical induction, philosophy of science and its relation to the information technology sciences, and case studies of information technology research. Prerequisites STAT 554. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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OR 763 - Research Methods in Systems Engineering and Information Technology
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OR 774: Advanced Dynamic Programming
3.00 Credits
George Mason University
Credits: 3 Cross-Listed with IT 774 Covers advanced topics on the theory and practice of dynamic programming, i.e., optimal sequential decision making over time in the presence of uncertainties. Stresses the mathematical foundations and introduces the theory, computational aspect, and applications of dynamic programming for deterministic and stochastic problems. Prerequisites OR674/SYST674 or permission of instructor.
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OR 774 - Advanced Dynamic Programming
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OR 780: Queuing Modeling of Computer-Communication Networks
3.00 Credits
George Mason University
Credits: 3 Cross-Listed with IT 780 Studies analytical modeling of computer and communication networks and performance evaluations. Topics include Markovian systems, open networks, closed networks, approximations, decomposition, simulation, sensitivity analysis, and optimal operation of systems. Presents local area networks, manufacturing systems, and other applications. Prerequisites OR 645 or 647, or ECE 542; or equivalent. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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OR 780 - Queuing Modeling of Computer-Communication Networks
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OR 782: Advanced Topics in Combinatorial Optimizations
3.00 Credits
George Mason University
Credits: 3 Cross-Listed with IT 782 Studies problems using most recent developments. Topics include cutting plane procedures based on polyhedral combinatorics; column-generation procedures for large, complex problems; heuristic approaches such as genetic algorithms, simulated annealing, and tabu search; study of special structures; reformulation techniques; and bounding approaches. Topics stress most recent developments in field. Prerequisites OR 641 and 642. Notes May be repeated for credit when topics are distinctly different. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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OR 782 - Advanced Topics in Combinatorial Optimizations
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OR 783: Advanced Topics in Network Optimization
3.00 Credits
George Mason University
Credits: 3 Cross-Listed with IT 783 Recent developments in solving optimization problems on networks. Prepares doctoral students to perform advanced research on network-related problems. Topics include linear, discrete, nonlinear, and stochastic problems. Several aspects of problems also studied, including computational complexity, exact algorithms, heuristics, solvable special cases, and computer implementation issues. Prerequisites OR 643. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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OR 783 - Advanced Topics in Network Optimization
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OR 784: Advanced Topics in Nonlinear Programming
3.00 Credits
George Mason University
Credits: 3 Cross-Listed with IT 784 Studies theory and algorithms for solving nonlinear optimization problems. Contents vary; possible topics include large-scale and parallel-unconstrained optimization, theoretical issues in constrained optimization, duality theory, Lagrangian and sequential quadratic programming methods. Prerequisites OR 644. Notes May be repeated for credit when topics are distinctly different. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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OR 784 - Advanced Topics in Nonlinear Programming
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OR 842: Models of Probabilistic Reasoning
3.00 Credits
George Mason University
Credits: 3 Cross-Listed with IT 842, SYST 842 Survey of alternative views about how incomplete, inconclusive, and possibly unreliable evidence might be evaluated and combined. Discusses Bayesian, Baconian, Shafer-Dempster, and Fuzzy systems for probabilistic reasoning. Prerequisites STAT 544 or OR 681, or permission of the instructor. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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OR 842 - Models of Probabilistic Reasoning
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OR 888: Distributed Estimation and Multisensor Tracking and Fusion
3.00 Credits
George Mason University
Credits: 3 Cross-Listed with SYST 888/IT 888/ECE 753 Centralized and distributed estimation theory, hierarchical estimation, tracking and data association, multisensor multitarget tracking and fusion, distributed tracking in distributed sensor networks, track-to-track association and fusion, and Bayesian networks for fusion. Prerequisites ECE 734 or SYST 611. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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OR 888 - Distributed Estimation and Multisensor Tracking and Fusion
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