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. Emphasis is on 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
Conceptual and theoretical foundations of mathematical programming techniques. A brief review of linear programming and the simplex method is followed by developments in duality theory and post-optimality analysis. Special methods to solve large-scale problems are presented. Nonlinear programming methods are introduced. Combinatorial analysis is introduced with particular focus on solving integer programming problems.

SYS 605 - (3) (Y)
Stochastic Systems
Prerequisites: APMA 310, APMA 312, or equivalent
An in-depth introduction to stochastic systems theory and applications in systems engineering. Markov chains, Poisson processes, birth and death processes, renewal processes, martingales, Brownian motion, 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. Emphasis is given to the properties of mathematical representations of systems, to the methods used to analyze mathematical models, and to 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, and state-variable methods and concepts from modern control theory. Applications are drawn from social, economic, managerial, and physical systems.

SYS 614 - (3) (Y)
Decision Analysis
Prerequisite: SYS 605 or equivalent
Principles and procedures of decision making under uncertainty and with multiple objectives. Subjective probability, Bayesian inference, preference orders, utility functions, measurement methods, principles of rationality, optimal decision procedures, value of information. Structuring and modeling decision problems: decision trees, influence diagrams, mathematical representations. Bayesian decision analysis, multiobjective decision analysis, sequential decision analysis, and group decision making.

SYS 616 - (3) (Y)
Knowledge-Based Systems
Prerequisite: APMA 310 or equivalent
Introduces the fundamental concepts for research, design, development and implementation of knowledge-based systems. Emphasis is on the foundations of artificial intelligence, problem solving, search, and decision making with a view toward real world applications. Students are required to develop a working knowledge-based system in a realistic application 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: Mathematical basis for risk assessment and management-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
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
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. The 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. Focus is 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
Philosophy, theory, methodology, and applications of systems engineering provide themes for this seminar-type course 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. This is 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 the synthesis of time series, data into forecasting models. The statistical basis of forecasting models 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
Decomposition, optimization, and control of hierarchical multi-level systems. Topics covered include application of optimization theory to large-scale systems, Dantzig-Wolfe decomposition and Benders algorithm, planning and coordination with prices and quantities, input-output analysis and material balancing, distribution of information in hierarchies, incentive compatible control, non-convex programming. Emphasis is placed on real-world planning problems.

SYS 752 - (3) (IR)
Sequential Decision Processes
Prerequisites: SYS 605, SYS 614, or equivalent
Stochastic sequential decision models and their applications. Sequential stochastic control theory. Dynamic programming. Finite horizon, infinite horizon discounted total cost, infinite horizon undiscounted total cost, and average expected cost Markov decision processes. Problems with imperfect state information. Computational aspects and suboptimal control. Vector criterion Markov decision processes. Examples: inventory control, maintenance, portfolio selection, water resource management, sequential decision aiding, linear-quadratic-Gaussian problems, signal detection (military and health care applications).

SYS 754 - (3) (IR)
Multiobjective Optimization
Prerequisites: SYS 603, SYS 614, or equivalent
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, 605, and 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
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: 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)
Thesis
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)
Dissertation
Formal record of student commitment to doctoral research under the guidance of a faculty advisor. Registration may be repeated as necessary.

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