9: School of Graduate Engineering and Applied Science

General Information | Degree Programs | Program Descriptions | Course Descriptions | Faculty

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Systems Engineering

SYS 601 - (3) (Y)
Introduction to Systems Engineering

Prerequisite: Admission to the graduate program
An integrated introduction to systems methodology, design, and management. An overview of systems engineering as a professional and intellectual discipline, and its relation to other disciplines such as operations research, management science, and economics. An introduction to selected techniques in systems and decision sciences, including mathematical modeling, decision analysis, risk analysis, and simulation modeling. Overview of contemporary topics relevant to systems engineering, such as reengineering and total quality management. Elements of systems management, including decision styles, human information processing, organizational decision processes, and information system design for planning and decision support. Emphasizes relating theory to practice via written analyses and oral presentations of individual and group case studies.

SYS 603 - (3) (Y)
Mathematical Programming

Prerequisite: SYS 321 or equivalent
Study of the conceptual and practical foundation of mathematical modeling and optimization, with emphasis on problem formulation and practical solution techniques. Coverage includes linear programs, nonlinear programs, combinatorial models, optimality conditions, and search strategies and algorithms. Topics are illustrated through the analysis of classic models from systems engineering and through the use of case studies. A variety of applications from engineering, biological systems, social science, and operations research are explored.

SYS 605 - (3) (Y)
Stochastic Systems

Prerequisites: APMA 310, APMA 312, or equivalent
Topics include a review of probability theory and applications of probabilistic models in systems engineering; introduction to stochastic systems theory, including Markov chains, Poisson processes, birth and death processes, renewal processes, stationary processes and ergodic theory; survey of stochastic models and applications, including queuing models, inventory models, storage models, and time series models.

SYS 612 - (3) (IR)
Dynamic Systems

Prerequisite: APMA 206 or equivalent
An introduction to the modeling, analysis, and control of dynamic systems, using ordinary differential and difference equations. Emphasizes the properties of mathematical representations of systems, the methods used to analyze mathematical models, and the translation of concrete situations into appropriate mathematical forms. Primary coverage includes ordinary linear differential and difference equation models, transform methods and concepts from classical control theory, state-variable methods and concepts from modern control theory, and continuous system simulation. Applications are drawn from social, economic, managerial, and physical systems.

SYS 614 - (3) (Y)
Decision Analysis

Prerequisite: SYS 605 or equivalent
Analysis of the principles and procedures of decision making under uncertainty and with multiple objectives; introduction to stochastic optimal control and dynamic programming. Representation of problems as decision trees and influence diagrams; corresponding solution methodologies; sensitivity analysis, Bayesian decision analysis, subjective probability, value of information, Monte Carlo simulation, value and utility theory, including the case of multiple objectives, nonbayesian approaches; introduction to Markov decision processes and neuro-dynamic programming for large scale and complex decision problems.

SYS 616 - (3) (Y)
Knowledge-Based Systems

Prerequisite: APMA 310 or equivalent
Introduces the fundamental concepts necessary for successful research in, and real world application of, knowledge-based systems. Emphasizes expert systems, hybrid expert systems (e.g., methods combining such tools as expert systems, neural networks, math programming, and genetic programming). Students are required to develop and validate a working knowledge-based system in a nontrivial domain. Cross-listed as CS 616.

SYS 634 - (3) (Y)
Discrete-Event Stochastic Simulation

Prerequisites: SYS 605 or equivalent
A first graduate course on the theory and practice of discrete-event simulation. Coverage includes the dynamics of discrete-event stochastic systems, simulation logic and computational issues, random number generation, specification of input probability distributions, output analysis, and model verification and validation. Emphasizes modern simulation programming languages including animation on microcomputers. Applications in manufacturing, transportation, communications, computer, and service systems.

SYS 650 - (3) (IR)
Risk Analysis

Prerequisites: APMA 310, SYS 321, or equivalent
A study of problems and complexities involved in risk assessment and management. Part I: Conceptualization—the nature of risk, the perception of risk, the epistemology of risk, and the process of risk assessment. Part II: Systems engineering tools for risk analysis—basic concepts in probability and statistics, decision analysis, and multiobjective decision making. Part III: Methodologies and techniques for risk analysis, focusing on the statistics of extremes.

SYS 670 - (3) (IR)
Environmental Systems Analysis

Prerequisites: SYS 321, SYS 360, SYS 402, or equivalent
Analysis of the application of systems engineering techniques to environmental planning and policy issues. Decision problems in water resources, air pollution, solid waste, and energy are examined. Problems of coping with natural and man-made hazards are highlighted. Among techniques emphasized are cost-benefit analysis, risk assessment and analysis, multiobjective decision analysis, conflict analysis, mathematical programming, simulation, and heuristic methods.

SYS 674 - (3) (Y)
Total Quality Engineering

Prerequisite: Basic statistics or permission of instructor
Topics include the comprehensive study of quality engineering techniques; characterization of Total Quality Management philosophy and continuous improvement tools; statistical monitoring of processes using control charts; process improvement using experimental design.

SYS 681, 682 - (3) (IR)
Selected Topics in Systems Engineering

Prerequisites: As specified for each offering
Detailed study of a selected topic, determined by the current interest of faculty and students. Offered as required.

SYS 693 - (Credit as arranged) (S)
Independent Study

Detailed study of graduate course material on an independent basis under the guidance of a faculty member.

SYS 695 - (Credit as arranged) (S)
Supervised Project Research

Formal record of student commitment to project research under the guidance of a faculty advisor. Registration may be repeated as necessary.

SYS 702 - (3) (SS)
Case Studies in Systems Engineering

Prerequisites: SYS 601, SYS 603, and SYS 605
Under faculty guidance, students apply the principles of systems methodology, design, and management along with the techniques of systems and decision sciences to systems analysis and design cases. Primary goal is the integration of numerous concepts from systems engineering using real-world cases. Focuses on presenting, defending, and discussing systems engineering projects in a typical professional context. Cases span a broad range of applicable technologies and involve the formulation of the issues, modeling of decision problems, analysis of the impact of proposed alternatives, and interpretation of these impacts in terms of the client value system. Cases are extracted from actual government, industry, and business problems, and they must be completed by the students in a time-constrained environment and with available resources.

SYS 716 - (3) (Y)
Artificial Intelligence

Prerequisite: SYS 616 or CS 616
In-depth study of a few major areas historically considered to be part of artificial intelligence. In particular, detailed coverage is given to the design considerations involved in the following applications: automatic theorem proving, natural language understanding and machine learning.

SYS 721 - (3) (IR)
Research Methods in Systems Engineering

Corequisites: SYS 601, SYS 603, SYS 605, or equivalent
Study of the philosophy, theory, methodology, and applications of systems engineering provide themes for this seminar in the art of reading, studying, reviewing, critiquing, and presenting scientific and engineering research results. Applications are drawn from water resources, environmental, industrial and other engineering areas. Topics discussed and papers reviewed are selected at the first meeting. Throughout the semester, students make a one-hour presentation of their chosen paper, followed by a one and one-half hour discussion, critique, evaluation, and conclusions regarding the topic and its exposition. Students are expected to read every paper before it is presented. Class size is limited.

SYS 730 - (3) (IR)
Time Series Analysis and Forecasting

Prerequisites: SYS 605, or equivalent
An in-depth study of time series analysis and forecasting models from a statistical and engineering perspective. The process of stochastic model building including model identification, estimation, and model diagnostic checking. A survey of forecasting models and applications including empirical models (smoothing methods and decomposition methods), regression models (simple and multiple regression, and econometric models), and ARIMA models (including seasonal models).

SYS 734 - (3) (IR)
Advanced System Simulation

Prerequisites: SYS 605 and SYS 634, or equivalent
Seminar on contemporary topics in discrete-event stochastic simulation. Topics determined by student and faculty interests. Topics may include model and simulation theory, validation, experiment design, output analysis, variance-reduction techniques, simulation optimization, perturbation analysis, parallel and distributed simulation, intelligent simulation systems, animation and output visualization.

SYS 742 - (3) (IR)
Heuristic Search

Prerequisites: SYS 605, or permission of instructor
Characterization and analysis of problem solving strategies that are guided by heuristic information. Course links material from optimization, intelligence systems, and complexity analysis. Formal development of the methods and complete discussion of applications, theoretical properties, and evaluation. Methods discussed include best-first strategies for OR and AND/OR graphs, simulated annealing, genetic algorithms and evolutionary programming, tabu search, and tailored heuristics. Applications of these methods to engineering design, scheduling, signal interpretation, and machine intelligence.

SYS 750 - (3) (IR)
Advanced Methods in Optimization

Prerequisites: SYS 603 or equivalent
Study of advanced topics in optimization on mathematical programming. Specific topics are determined by the interests of faculty and students, but may include: network and graph algorithms, decomposition methods for large-scale programming, stochastic optimization, and interior-point methods.

SYS 752 - (3) (IR)
Sequential Decision Processes

Prerequisites: SYS 605, SYS 614, or equivalent
Analysis of stochastic sequential decision models and their applications; sequential stochastic control theory; dynamic programming; finite horizon, infinite horizon models; discounted, undiscounted, and average cost models; Markov decision processes, including stochastic shortest path problems; problems with imperfect state information; stochastic games; computational aspects and suboptimal control, including neuro-dynamic programming; examples: inventory control, maintenance, portfolio selection, optimal stopping, water resource management, linear quadratic Gaussian problems, sensor management.

SYS 754 - (3) (IR)
Multiobjective Optimization

Prerequisites: SYS 603, SYS 614, or equivalent
Analysis of the theories and methodologies for optimization making with multiple objectives under certainty and uncertainty; structuring of objectives, selection of criteria, modeling and assessment of preferences (strength of preference, risk attitude, and tradeoff judgments); vector optimization theory and methods for generating nondominated solutions. Methods with prior assessment of preferences, methods with progressive assessment of preferences (iterative-interactive methods), methods allowing imprecision in preference assessments; group decision making; building and validation of decision-aiding systems.

SYS 763 - (3) (IR)
Response Surface Methods for Product and Process Design

Prerequisites: SYS 601, SYS 605, and SYS 674, or permission of instructor
Response surface and other methods provide engineering design and process improvement through the collection and analysis of data from controlled experimentation. Response surface methods use experimental data to construct and explore the relationship between design variables and measures of product or process performance. This course investigates the construction of response models for systems with discrete and continuous valued responses. Both practical and theoretical aspects of modeling are explored.

SYS 770 - (3) (IR)
Sequencing and Scheduling

Prerequisites: SYS 603, SYS 605, or equivalent
A comprehensive treatment of scheduling theory and practice. The formal machine-scheduling problem: assumptions, performance measures, job and flow shops, constructive algorithms for special cases, disjunctive and integer programming formulations, branch-and-bound and dynamic programming approaches, computational complexity and heuristics. Alternative scheduling paradigms. Scheduling philosophies and software tools in modern manufacturing applications.

SYS 775 - (3) (IR)
Forecast-Decision Systems

Prerequisites: SYS 605, SYS 614, or equivalent
Analysis of the Bayesian theory of forecasting and decision making; judgmental and statistical forecasting, sufficient comparisons of forecasters, verification of forecasts, combining forecasts; optimal and suboptimal decision procedures using forecasts including static models, sequential decision models, stopping-control models; economic value of forecasts; communications of forecasts; design and evaluation of a total forecast-decision system.

SYS 781, 782 - (3) (IR)
Advanced Topics in Systems Engineering

Prerequisites: As specified for each offering
Detailed study of an advanced or exploratory topic. The topic determined by the current interest of faculty and students. Offered as required.

SYS 793 - (Credit as arranged) (S)
Independent Study

Detailed study of graduate course material on an independent basis under the guidance of a faculty member.

SYS 796 - (1) (S)
Systems Engineering Seminar

Regular meeting of graduate students and faculty for presentation and discussion of contemporary systems problems and research. Offered for credit each semester. Registration may be repeated as necessary.

SYS 895 - (Credit as arranged) (S)
Supervised Project Research

Formal record of student commitment to project research for Master of Engineering degree under the guidance of a faculty advisor. Registration may be repeated as necessary.

SYS 897 - (Credit as arranged) (S)
Graduate Teaching Instruction

For master’s students.

SYS 898 - (Credit as arranged) (S)

Formal record of student commitment to master’s research under the guidance of a faculty advisor. Registration may be repeated as necessary.

SYS 997 - (Credit as arranged) (S)
Graduate Teaching Instruction

For doctoral students.

SYS 999 - (Credit as arranged) (S)

Formal record of student commitment to doctoral research under the guidance of a faculty advisor. May be repeated as necessary.

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