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  • OR 540: Management Science

    3.00 Credits
    George Mason University

    Credits: 3 Cross-Listed with SYST 540 Operations research techniques and their application to managerial decision making. Mathematical programming, Markov processes, queuing theory, inventory models, PERT, CPM, and computer simulation are covered, as well as use of contemporary computer software for problem solving. Case-study approach to problem solving is used. Prerequisites MATH 108, and STAT 250 or OM 200; or equivalent. Notes OR/MS and SE/MS majors do not receive credit. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0 When Offered F, S
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  • OR 541: Operations Research:Deterministic Models

    3.00 Credits
    George Mason University

    Credits: 3 Survey of deterministic methods of solving real world decision problems. Covers linear programming model and simplex method of solution, duality, and sensitivity analysis, transportation and assignment problems; shortest path, minimal spanning tree, and maximal flow problems; and an introduction to integer and nonlinear programming. Emphasis on modeling and problem solving. Prerequisites MATH 203 or equivalent. Notes Students who have taken OR 441/MATH 441 will not receive credit. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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  • OR 542: Operations Research:Stochastic Models

    3.00 Credits
    George Mason University

    Credits: 3 A survey of probabilistic methods for solving decision problems under uncertainty, probability theory review, reliability, queuing theory, inventory systems, Markov chain models, and simulation. Emphasis on modeling and problem solving. Prerequisites STAT 344 or MATH 351, or equivalent. Notes Students who have taken OR 442/MATH 442 do not receive credit. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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  • OR 574: Quality Control and Process Management

    3.00 Credits
    George Mason University

    Credits: 3 Cross-Listed with SYST 574 An overview of quality control techniques widely used in a number of manufacturing industries. The course teaches students about combining engineering process quality management and traditional statistical quality control procedures that are applicable in industry and are based on contemporary technologies such as lean Six Sigma, total quality management and predictive maintenance for achieving superior quality, reliability and maintainability. Prerequisites Graduate standing or permission of instructor.
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  • OR 576: Manufacturing Systems Analysis

    3.00 Credits
    George Mason University

    Credits: 3 Cross-Listed with SYST 576 An overview of modeling and analysis of general manufacturing systems techniques widely used in a number of manufacturing industries, such as semiconductor manufacturing. The course teaches students about best scheduling and inventory control practices, enterprise resource management principles, and details of engineering economy that are applicable in the industry. Prerequisites Graduate standing or permission of instructor.
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  • OR 635: Discrete System Simulation

    3.00 Credits
    George Mason University

    Credits: 3 Computer simulation as a scientific methodology in operations analysis, with emphasis on model development, implementation, and analysis of results. Discrete-event models, specialized software, input modeling, and output statistics are covered. Extensive computational work is required. Prerequisites OR 542, or STAT 354 or 344, or equivalent; and knowledge of scientific programming language. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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  • OR 640: Global Optimization and Computational Intelligence

    3.00 Credits
    George Mason University

    Credits: 3 Introduction to global optimization of nonconvex mathematical programs and numerical methods for the solution of such problems. Topics covered include high-level survey of traditional mathematical programming algorithms; critical comparison of metaheuristics and artificial intelligence (AI) algorithms to traditional mathematical programming algorithms; probabilistic search, multistart methods, statistical tests of performance and confidence, simulated annealing, genetic algorithms, neural networks, Tabu search, homotopies and tunneling; the traveling salesman problem, the Steiner problem, Stackelberg-Cournot-Nash mathematical games and other classical nonconvex optimization problems. Prerequisites MATH 203 or equivalent, and knowledge of a scientific programming language. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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  • OR 641: Linear Programming

    3.00 Credits
    George Mason University

    Credits: 3 In-depth look at the theory and methodology of linear programming: Computational enhancements of the revised simplex method; sparse-matrix techniques, bounded variables and the dual simplex method. Alternative interior point methods described and computational complexity of various algorithms analyzed. Prerequisites OR 541, or permission of instructor. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0 When Offered F
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  • OR 642: Integer Programming

    3.00 Credits
    George Mason University

    Credits: 3 Cutting plane and enumeration algorithms for solution of integer linear programs; bounding strategies and reformulation techniques; heuristic approaches to the solution of complex problems; knapsack problems, matching problems, set covering and partitioning problems; applications to problems in OR/MS, such as capital budgeting, facility location, political redistricting, engineering design, and scheduling. Prerequisites OR 541, or permission of instructor. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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  • OR 643: Network Modeling

    3.00 Credits
    George Mason University

    Credits: 3 Introduction to network problems in operations research, computer science, electrical engineering, and systems engineering. Solution techniques for various classes of such problems are developed. Topics include minimal-cost network flow, maximal flow, shortest path, and generalized networks; plus stochastic networks, network reliability, and combinatorially based network problems. Complexity of each problem class analyzed. Prerequisites OR 541, or permission of instructor. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0 When Offered F
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