All courses offered in the School of Engineering and Applied Science are identified by the two- or three-letter prefix code, designating the general subject area of the course, followed by a four-digit number. The first digit specifies the approximate level of the course as follows: 7 – graduate, and 8 – advanced graduate. The second digit denotes the term hours associated with the course. The last two digits specify the course numbers. Thus, CSE 7320 denotes a course offered by the Department of Computer Science and Engineering at the (7) graduate level, having three term hours, and having the course number 20. The prefix codes are as follows:
CSE Department of Computer Science and Engineering
EE Department of Electrical Engineering
EMIS Department of Engineering Management, Information, and Systems
ENV Department of Environmental and Civil Engineering
ME Department of Mechanical Engineering
SS Special Studies
ENGINEERING MANAGEMENT, INFORMATION, AND SYSTEMS
Associate Professor Barr, Chair
Professor: Kennington; Associate Professor: Helgason;
Assistant Professor: Olinick; Senior Lecturer: Stracener;
Lecturer: Lillard; Adjunct
Faculty: Arunski, Dean, Gorman,
Hinderer, Lacy, Pickels, Siems, Zaki.
The department offers graduate programs in engineering management, operations research, and systems engineering. Faculty specializations include …, and mathematical programming.
Degrees
Master of Science (Major in Operations Research)
Master of Science (Major in Systems Engineering)
Master of Science in Engineering Management
Ph.D. (Major in Operations Research)
D. Eng. (Major in Engineering Management)
Students in the Department of Engineering Management, Information, and Systems (EMIS)have access to a wide range of facilities and equipment. The department’s computing environment has evolved to an Ethernet-based network of workstations from Sun Microsystems, Compaq, and DEC (Digital Equipment Corporation).
Master of Science
(Major in Operations Research)
Director: Kennington
Professors: Bhat, Matula; Associate Professor: Barr, Helgason; Assistant Professor:
Olinick; Adjunct Faculty: Gorman, Siems, Zaki.
Operations research is the study of technical and analytical tools for management decision making. The growth of the field is closely linked to developments in computing capabilities. The analyst must have a solid working knowledge of computers to manage and process enormous amounts of information vital to the daily activities of a modern complex organization. The program is designed to prepare graduates for industrial opportunities in management consulting, transportation, telecommunications, defense, manufacturing, and the service industries. This program is offered both on campus and off campus via several remote delivery systems; the Master’s degree may be completed using the TAGER television microwave sys-tem serving the North Texas area. Individual courses may be taken by satellite transmission via the National Technological University. See the Off-Campus Education section for more information on off-campus delivery systems.
Admission Requirements
• Bachelor of Science in mathematics or computer science, or in one of the engineering disciplines.
• G.P.A. of at least 3.00 on a 4.00 scale in previous undergraduate and graduate study.
• Submission of official Graduate Record Examination (GRE) test results with a minimum 80th-percentile quantitative score.
Degree Requirements
• Thirty (30) term-credit hours of graduate courses with a minimum graduate G.P.A. of 3.00 on a 4.00 scale.
• A minimum of fifteen (15) term-credit hours numbered 6000 or above.
• Satisfactory completion of one (1) of the following core courses:
EMIS 7370 Probability
and Statistics for Scientists and Engineers
EMIS 7377 Statistical
Design and Analysis of Experiments
and the following three (3) additional core courses:
EMIS 7362 Production
Management
EMIS 8360 Operations
Research Models
EMIS 8371 Linear
Programming
• Satisfactory completion of three (3) of the following depth courses:
EMIS 7361 Simulation
EMIS 8370 Stochastic
Models
EMIS 8372 Queuing
Theory
EMIS 8373 Integer
Programming
EMIS 8374 Network
Flows
EMIS 8378 Optimization
Models
EMIS 8381 Nonlinear
Programming
• Satisfactory completion of three (3) elective courses, approved by the adviser, in business, computer science, engineering, mathematics, or statistics.
Master of Science
(MAJOR IN systems engineering)
Director: Stracener
Professors:
Bhat (Statistical Science),
Kennington, Packman (Mechanical Engineering); Associate Professors: Barr, Helgason; Assistant Professors: Olinick, Tian (Computer Science and Engineering); Lecturer: Coyle; Adjunct
Faculty: Arunsky, Dean, Lacy, Oshana.
The goal of systems engineering is development and management of systems (products and services) that satisfy customer requirements considering engineering, technology, environmental, management risk, and economic factors by viewing the system as a whole, over its life cycle. Systems engineering is also the practice of ‘good engineering.’ Through systems engineering and related courses, the student gains exposure to a variety of topics such as reliability, quality, logistics/supply webs, operations research, engineering management, software engineering, telecommunications and environmental engineering. ‘Systems thinking’ skills are developed which foster more effective practice for the engineer or engineering manager within the business enterprise. The systems engineering program’s objective is to make you a better engineer or manager by imparting an enhanced understanding of the impact of your engineering decisions, and the impact of other decisions on you.
The program has been developed in response to the growing need by industry and government for engineers who are not only specialists in a particular area, but who have a systems perspective in order to more effectively practice engineering and manage within the business enterprise. The program offers flexibility for: (1) systems engineers who are entering the field, updating skills or acquiring new skills, (2) engineers who need to acquire a broadening of their technical and management education from systems perspective, (3) engineers with upper-level management aspirations and (4) engineering students seeking to increase their market value by acquiring knowledge and skills necessary for engineering of products and services from a systems perspective.
The Systems Engineering Program is designed to build on your engineering/technical education and experience to broaden your exposure while developing your problem definition and problem solving skills. The program is intended to fill a niche between core engineering specialization and a business program.
admission requirements
• Bachelor of Science in engineering, mathematics, or one of the quantitative
• G.P.A. of at least 3.00 out of 4.00 scale in previous undergraduate and graduate study.
• A minimum of two years of college-level mathematics, including at least one year of calculus.
degree requirements
• Thirty (30) term-credit hours of graduate courses with a minimum graduate G.P.A. of 3.00 on a 4.00 scale.
• Satisfactory completion of the core curriculum encompassing five (5) courses:
EMIS 7300 Systems Analysis Methods
EMIS 7301 Systems Engineering Process
EMIS 7303 Integrated Risk Management
EMIS 7305 Systems Analysis and Optimization
EMIS 7307 Systems Integration and Test
• Satisfactory completion of one (1) of the following tracks:
Systems Engineering Application Track.
1) Satisfactory completion of three (3) Group I Systems Engineering electives, with the approval of the student's academic adviser, in one of the following concentrations (Group I concentration must be in a different field from the undergraduate major):
Computer Science
Operations Research
Computer Engineering
Mechanical Engineering
Environmental Engineering
Manufacturing Engineering
Software Engineering
Engineering Management
Telecommunications
2) Satisfactory
completion of two (2) Group II electives. Group II electives require advisor
approval and may be selected from the graduate
offerings in the School of Engineering, the Edwin L. Cox School of Business,
and the Departments of Physics, Chemistry, Statistics, Mathematics, or
Economics in Dedman College. Neither of the two electives can be selected from
the student's field of concentration.
Systems Engineering Technology Track.
1) Satisfactory completion of three (3) Group I Systems Engineering electives
EMIS 7310 Systems
Engineering Design
EMIS 7312 Software Systems
Engineering
EMIS 7320 Systems
Engineering Management
EMIS 7330 Systems
Reliability Engineering
EMIS 7340 Logistics
Systems Engineering
2) Satisfactory completion of two (2) Group II electives. Group II electives require advisor approval and may be selected from systems relevant School of Engineering programs and courses.
Master of Science
in Engineering Management
Director: Barr
Faculty: Helgason, Kennington,
Olinick; Adjunct Faculty: Pickels, Siems, Stracener.
A special feature of the Engineering Management program is its interaction with allied areas such as operations research, mathematical science, engineering, computer science, and business administration. Excellent faculty members from these areas participate in the department’s activities, and students take courses from several areas depending upon their interests.
Courses in this program are available on and off campus via several remote delivery systems. The Master’s degree may be completed using the TAGER television microwave system serving the North Texas area, or by videotape in other areas. Individual courses may be taken by satellite transmission via the National Technological University. See the Off-Campus Education section for more information.
Admission Requirements
• Bachelor of Science in one of the engineering disciplines.
• G.P.A. of at least 3.00 on a 4.00 scale in previous undergraduate and graduate study.
• Submission of official Graduate Record Examination (GRE) test results with a minimum 80th-percentile quantitative score.
Degree Requirements
• Thirty (30) term-credit hours of graduate courses with a minimum graduate G.P.A. of 3.00 on a 4.00 scale. Required work includes 15 TCH of core courses, six TCH of business courses, and nine TCH of electives. At least fifteen (15) hours must be completed at the 8000 level or above.
• Satisfactory completion of the following five (5) core courses:
EMIS
7362 Production Management
EMIS 7370 Probability and Statistics for
Scientists and Engineers
EMIS 8360 Operations Research Models
EMIS 8361 Economic Decision Analysis
EMIS 8364 Management for Engineers
• Satisfactory completion of two (2) business courses:
EMIS 8362 Engineering
Accounting
EMIS 8363 Engineering
Finance
• Satisfactory completion of three (3) elective courses, approved by the adviser, in business, computer science, engineering, mathematics, or statistics.
Doctor of Philosophy
(Major in Operations Research)
Admission Requirements
• Master’s degree in operations research, mathematics, computer science, or a related field. In the case of admission without a Master’s degree, the baccalaureate degree must be conferred prior to the time the student begins classes as a graduate student.
• G.P.A. of at least 3.40 on a 4.00 scale in the junior and senior years.
• Submission of official Graduate Record Examination (GRE) test results with a minimum 80th-percentile quantitative score.
Degree Requirements
• Fifty-four (54) term-credit hours beyond the baccalaureate degree, plus 24 TCH of dissertation credit. At least 21 TCH must be earned in a major concentration area. The student must also complete at least 12 hours of study in a departmental minor, and an additional 12 hours in a minor area outside the department. A course may not be counted toward more than one area. The minor requirements may be satisfied by transfer credit.
• The following courses, taken at SMU or credited from another graduate institution:
Operations
Research:
EMIS 7361 Computer
Simulation Techniques
EMIS 7362 Production
Management
EMIS 8360 Operations
Research Models
EMIS 8361
Economic Decision Analysis
EMIS 8370
Stochastic Models
EMIS 8371
Linear Programming
EMIS 8378
Optimization Models or EMIS 8381 Nonlinear Programming
Statistics:
STAT 6327 Mathematical
Statistics
Mathematics
(any two of the following):
MATH 5315
Introduction to Numerical Analysis
MATH 5316
Numerical Linear Algebra
MATH 5317
Mathematical Software
Computer
Science:
EMIS 7350 Algorithm
Engineering
• Satisfactory completion of the Preliminary Counseling Examination, a two-part oral exam covering operations research fundamentals and algorithms/computer science theory. Skills tested include those developed in EMIS courses 3358, 7350, 7370, 8360, 8361, and 8371. A reading list to help students prepare for the exam is available from the department office.
• Satisfactory completion of the Doctoral Qualifying Examination.
• Satisfactory completion and defense of the doctoral dissertation.
Doctor of Engineering
(Major in Engineering Management)
This degree is designed to provide students with preparation to meet doctoral standards in an applied science or engineering practice. Applied science as a focus for the doctoral degree refers to the study of advanced theory and its application to a practical problem in order to test and verify performance limitations. The degree requires a high level of expertise in the theoretical aspects of relevant scientific principles and experience with details of the implementation of theory on realistic problems. Engineering practice as a focus for the degree is the study of different aspects that play a role in the transfer of technology, from its inception in research to the intended engineering environment, as well as relevant economic issues.
For information on general degree requirements, see the “Doctor of Engineering Degree” section of this catalog.
Admission Requirements
• Bachelor of Science degree in an engineering discipline.
• A Master’s degree in a technical area, or in a managerial area such as business administration or economics.
• Submission of official Graduate Record Examination (GRE) test results with a minimum 80th-percentile quantitative score.
• Score of 600 or higher on the Test of English as a Foreign Language (TOEFL) or its equivalent, if English is not the native language.
• Approval of the Director of the Engineering Management Graduate Program.
Degree Requirements
• Twenty-four (24) term hours of Engineering Management. These hours must come from graduate-level courses in quantitative and qualitative aspects of managing in a modern technical environment. Courses in the areas of engineering management, management science, operations research, operations management, production management, and other related fields may qualify. All graduate courses in engineering management in the Computer Science and Engineering Department are acceptable for this category.
• Eighteen (18) term hours in a technical specialty. These hours must be taken in an engineering or other technical area consistent with anticipated doctoral work demands.
• Nine (9) term hours of Business/Economics. These hours must come from courses in a graduate program. They should expand the student’s understanding of the economic issues and problems relating to the transfer and management of technology.
• Fifteen (15) term hours of electives. All elective hours must come from graduate-level courses and must be approved by the advisory committee. These courses should, in some way, complement and strengthen the student’s degree plan.
• Twelve (12) term hours of Praxis. These hours must be taken in residence. The student enrolls for these hours in the course of preparing the praxis project.
• The following courses, or their equivalents, included in the degree plan:
Engineering
Management:
EMIS 7362 Production Management
EMIS 8361 Economic Decision Analysis
EMIS 8362 Engineering Accounting
EMIS 8363 Engineering Finance
EMIS
8364 Management for Engineers
Operations
Research:
EMIS 8360 Operations Research Models
EMIS 8378 Optimization Models for Decision Support
and
one of the following:
EMIS 8371 Linear Programming
EMIS 8373 Integer Programming
EMIS 8374 Network Flows
Statistics:
EMIS
7370 (STAT 5340) Probability and Statistics for Scientists and Engineers
EMIS 7377 (STAT 5377) Statistical Design and Analysis of Experiments
A course may not be counted toward more than one category. The minor requirements may be satisfied by transfer credit.
• Satisfactory completion of the Preliminary Counseling Examination, an oral exam covering degree fundamentals. The exam should be scheduled after the student has taken courses in production management, management for engineers, economic decision analysis, and operations research models, but before 24 term hours have been completed. Questions are drawn predominantly from the graduate courses EMIS 7362, 8360, 8361, and 8364. If the student fails the exam, he or she may retake it once. Since the exam’s goal is to detect weak-nesses in the student’s background, the examiners may grant a conditional or partial pass. Such a pass indicates that the student’s weaknesses can be over-come by taking specific courses. In this situation, the student need not retake the exam but will be required to take one or more courses and achieve a grade of B or better.
• Satisfactory completion of the Doctoral Qualifying Examination.
• Satisfactory completion and defense of the doctoral praxis.
The Courses (EMIS)
7301. Systems Engineering Process. The discipline, theory, economics, and methodology of systems engineering is examined. The historical evolution of the practice of systems engineering is reviewed, as are the principles that underpin modern systems methods. The economic benefits of investment in systems engineering and the risks of failure to adhere to sound principles are emphasized. An overview perspective distinct from the traditional design- and analytical-specific disciplines is developed.
7303. Integrated Risk Management. An introduction to risk management based upon integrated trade studies of program performance, cost, and schedule requirements. Topics include risk planning, risk identification and assessment, risk handling and abatement techniques, risk impact analysis, management of risk handling and abatement, and subcontractor risk management. Integrated risk management methods, procedures, and tools will be examined.
7304. (ENV 7304) Technical Communications. Both oral and written communications skills for engineers: engineering documents and writing standards, audience analysis, graphics, collaborative skills, and ethical issues. Credit is not allowed for both EMIS 5304 and the same course offered by another department. Prerequisite: Junior standing in engineering.
7305. System Optimization and Analysis. Emphasis is placed on the systems analysis process as the rational basis for developing optimum products consistent with customer requirements. Specific topics include requirements analysis, effectiveness analysis, operational analysis, environmental analysis, and life cycle analysis. Modeling and optimization techniques are introduced as necessary.
7306. (CSE 7306) Technical Entrepreneurship. Development of principles and practical strategies for the management and evolution of rapidly growing technical endeavors. Credit is not allowed for both EMIS 5306 and the same course offered by another department. Prerequisite: Junior standing.
7307. System Integration and Test. The process of successively synthesizing and validating larger and larger segments of a partitioned system within a controlled and instrumented framework is examined. System integration and test is the structured process of building a complete system from its individual elements and is the final step in the development of a fully functional system. The significance of structuring and controlling integration and test activities is stressed. Formal methodologies for describing and measuring test coverage, as well as sufficiency and logical closure for test completeness, are presented. Interactions with system modeling techniques and risk management techniques are discussed. The subject material is based upon principles of specific engineering disciplines and best practices, which form a comprehensive basis for organizing, analyzing, and conducting integration and test activities.
7308. Engineering Management. This course examines planning, financial analysis, organizational structures, management of the corporation (including its products, services, and people), transfer of ideas to the marketplace, and leadership skills. Credit is not allowed for both EMIS 5308 and the same course offered by another department. Prerequisite: Junior standing.
7309. Information Engineering and Global Perspectives. This course examines global and information aspects of technology- and information-based companies. Credit is not allowed for both EMIS 5309 and the same course offered by another department. Prerequisite: Junior standing.
7312. Software Systems Engineering. The course focuses on the engineering of complex systems that have a strong software component. For such systems, software often assumes functions previously allocated to mechanical and electrical subsystems, changing the way systems engineers must think about classical systems issues. The course provides a framework for addressing systems engineering issues by focusing on the Software Engineering Institute’s Systems Engineering Capability Maturity Model (SE-CMM). Topics include deriving and allocating requirements, system and software architectures, integration, interface management, configuration management, quality, verification and validation, reliability, and risk.
7317 (MATH 5317). Mathematical Software. Design and construction of numerical and symbolic software as stand-alone segments, packages and libraries. Examples: linear algebra, quadrature, optimization; MATLAB and MAPLE; NAG and IMSL libraries. Impact of computer architecture. Prerequisites: MATH 3315/EMIS 3365 or MATH 5315/EMIS 7365 or MATH 5316/EMIS 7366, a programming course (e.g., C or FORTRAN), and some knowledge of linear algebra, or permission of instructor.
7330 (CSE 7330). File Organization and Database Management. A survey of current database approaches and systems; principles of design and use of these systems. Query language design, implementation constraints. Applications of large databases. Includes a survey of file structures and access techniques. Use of a relational DBMS to implement a database design project. Pre-requisite: CSE 3358.
7350 (CSE 7350). Algorithm Engineering. Algorithm design techniques. Methods for evaluating algorithm efficiency. Data structure specification and implementation. Applications to fundamental computational problems in sorting and selection, graphs and networks, scheduling and combinatorial optimization, computational geometry, arithmetic and matrix computation. Introduction to parallel algorithms. Introduction to computational complexity and a survey of NP-complete problems. Prerequisite: CSE 3358 (for non-CSE graduate students: CSE 7311 or 3358).
7360. Management of Information Technologies. Defines the management activities of the overall computer resources within an organization or government entity. Consists of current topics in strategic planning of computer resources, budgeting and fiscal controls, design and development of information systems, personnel management, project management, rapid prototyping, and system life cycles.
7361. Computer Simulation Techniques. Introduction to the design and analysis of discrete probabilistic systems using simulation. Emphasizes model construction and a simulation language. Prerequisites: Programming ability, introduction to probability or statistics.
7362. Production Management. A survey of models and methods for designing and implementing quality-based, integrated production/distribution systems. Topics include demand forecasting, product mix decisions, distribution systems, facilities location and layout, scheduling, inventory and materials management, just-in-time, and quality control for manufacturing and service operations. Prerequisite: EMIS 3360 or 8360.
7363. Applied Parallel Programming. Surveys the theory and emphasizes the practice of developing efficient applications software for parallel computers. Topics include a survey of parallel processing architectures and machines, elements of parallel programming (process creation, synchronization, communication, and scheduling), alternative parallel programming schemes (languages and language enhancements), and implementation of scientific and industrial applications. Prerequisite: FORTRAN or C programming.
7364 (STAT 5344). Statistical Quality Control. A comprehensive introduction to the statistical quality-control methods that underlie the modern quality revolution. Statistics and simple probability are used to develop control charts, for monitoring and improving the quality of an ongoing process, and for acceptance-sampling plans (including MIL-STD). Control charts for attributes, variables, and Cusum procedures are defined and applied to everyday problems in manufacturing and service businesses.
7365 (MATH 5315). Introduction to Numerical Analysis. Numerical solution of linear and nonlinear equations, interpolation and approximation of functions, numerical integration, floating point arithmetic, and the numerical solution of initial valve problems in ordinary differential equations. Student use of the computer is emphasized. Prerequisites: FORTRAN and MATH 2343 or 3315.
7366 (MATH 5316). Numerical Linear Algebra. This course studies the efficient solution of linear systems by both direct and interactive methods. The concept of elementary matrix transformations is used to provide a unified treatment of direct methods. Stationary and conjugate direction methods are developed for efficiently solving sparse linear systems. Prerequisites: FORTRAN or MATLAB, MATH 3353, MATH 3315, or MATH 5315.
7369. Engineering Reliability. Topics include reliability, replacement and maintenance models, failure distributions and reliability functions, process and product control problems. 1 TCH Design. Prerequisite: EMIS 4340 or 5370.
7370 (STAT 5340). Probability and Statistics for Scientists and Engineers. Introduction to fundamentals of probability and distribution theory, statistical techniques used by engineers and physical scientists. Examples of tests of significance, operating characteristic curves, tests of hypothesis about one and two parameters, estimation, analysis of variance, and the choice of a particular experimental procedure and sample size. Prerequisite: MATH 2339 or equivalent.
7377 (STAT 5377). Statistical Design and Analysis of Experiments. Introduction to statistical principles in the design and analysis of industrial experiments. Completely randomized, randomized complete and incomplete block, Latin square, and Plackett-Burman screening designs. Complete and fractional experiments. Descriptive and inferential statistics. Analysis of variance models. Mean comparisons. Prerequisite: EMIS 4340 and senior standing with a science or engineering major, or permission of instructor.
8098. Seminar. The course consists of the seminars and colloquia given by the resident faculty and invited guests in various specialized as well as general topics in operations research, engineering management, systems engineering, and information engineering.
8330 (CSE 8330). Advanced Database Management Systems. An extensive investigation of distributed databases and implementation issues. Included are design, data replication, concurrency control, and recovery. Implementation project included. Prerequisite: EMIS 7330.
8331 (CSE 8331). Data Mining. This course introduces various data mining concepts and algorithms from a database perspective. A historical background and related topics are first discussed, followed by an overview of data mining core topics (classification, clustering, association rules) and more advanced topics (temporal and spatial data, scalability and parallelization, and outliers). Topics discussed include linear regression, distance measure, decision trees, and neural nets. Case studies and projects are included. Prerequisite: EMIS 7330.
8337 (CSE 8337). Information Retrieval. Examination of techniques used to store and retrieve unformatted/textual data. Examination of current research topics of data mining, data warehousing, digital libraries, hypertext, and multimedia data. Prerequisite: EMIS 7330.
8350 (CSE 8350). Algorithms II. Analysis of dynamic data structures, lower bound theory, problem equivalence and reducibility, complexity theory, probabilistic algorithms, machine models of sequential and parallel computation, parallel algorithms. Prerequisite: EMIS 7350.
8355 (CSE 8355). Graph Theory: Algorithms and Applications. Development of algorithmic and computational aspects of graph theory, with application of concepts and techniques to solving problems of: connectivity, set covering, scheduling, shortest paths, traveling salesmen, network flow, matching, and assignment. Prerequisite: EMIS 7350 or permission of instructor.
8360. Operations Research Models. A survey of models and methods of operations research. Deterministic and stochastic models in a variety of areas will be covered. Credit is not allowed for both EMIS 3360 and EMIS 8360. Prerequisites: A knowledge of linear algebra and an introduction to probability and statistics.
8361. Economic Decision Analysis. Introduction to economic analysis methodology. Topics include engineering economy and cost concepts, interest formulas and equivalence, economic analysis of alternatives, technical rate of return analysis, and economic analysis under risk and uncertainty. Prerequisite: Introductory probability.
8362. Engineering Accounting. An introduction to and overview of financial and managerial accounting for engineering management. Topics include basic accounting concepts and terminology; preparation and interpretation of financial statements; and uses of accounting information for planning, budgeting, decision-making, control, and quality improvement. The focus is on concepts and applications in industry today.
8363. Engineering Finance. Develops an understanding of corporate financial decisions for engineers. Topics include cost of capital, capital budgeting, capital structure theory and policy, working capital management, financial analysis and planning, and multinational finance. Prerequisite: EMIS 8361 or a knowledge of time value of money.
8364. Management for Engineers. How to manage technology and technical functions from a pragmatic point of view. How to keep from becoming technically obsolete as an individual contributor and how to keep the corporation technically astute. This course will look at the management of technology from three distinct viewpoints: 1) the management of technology from both an individual and a corporate perspective, 2) the management of technical functions and projects, and 3) the management of technical professionals within the organization. Pre-requisite: Graduate standing in engineering.
8370 (STAT 6376). Stochastic Models. Model building with stochastic processes in applied sciences. Phenomena with uncertain outcomes are formulated as stochastic models and their properties are analyzed. Specific problems come from areas such as population growth, queueing, reliability, time series, and social and behavioral processes. Statistical properties of the models are emphasized. Prerequisites: STAT 5373 and graduate standing.
8371. Linear Programming. A complete development of theoretical and computational aspects of linear programming. Prerequisite: MATH 3353.
8372 (STAT 6372). Queueing Theory. Analysis of stochastic service systems subject to random input. Markov and renewal process techniques are illustrated. Prerequisite: Any one of EE 7306, EMIS 8370, or STAT 6370, 6376, or 8379.
8373. Integer Programming. A presentation of algorithms for linear integer programming problems. Topics include complexity analysis, cutting plane techniques, and branch-and-bound. Prerequisite: EMIS 8360 or 8371.
8374. Network Flows. A presentation of optimization algorithms and applications modeling techniques for network flow problems. Topics include pure, generalized, integer, and constrained network problems, plus special cases of each, including transportation, assignment, shortest-path, transshipment, multicommodity, and nonlinear networks. Case studies illustrate the uses of network models in industry and government settings.
8378. Optimization Models for Decision Support. Study of the design and implementation of decision support systems based on optimization models. Course objectives: development of modeling skills, practice in the application of operations research techniques, experience with state-of-the-art software, and the study of decision support systems design and management. Topics include linear, integer, network, nonlinear, multi-objective, and stochastic optimization models for manufacturing, logistics, telecommunications, service operation, and public sector applications.
8381. Nonlinear Programming. Topics include convexity analysis, nonlinear duality theory, Kuhn-Tucker conditions, algorithms for quadratic programming, separable programming: gradient and penalty methods. Prerequisite: EMIS 8371.
8382. Theory of Optimization. Lagrange multiplier theory, fixed-point representations. Duality/convex analysis/subgradient relationship. Prerequisite: EMIS 8371.
8(0-4)90, 8(0-4)93. Graduate Seminar. Special and intensive study of selective topics in operations research, engineering management, systems engineering, or information engineering, aimed at encouraging students to follow recent developments through regular critical reading of the literature.
8(1-4)94, 8(1-4)95. Selected Problems. Independent investigation of topics in operations research, engineering management, systems engineering, and information engineering approved by the department chair and by the major professor. Prerequisite: 12 semester hours of graduate credit.
7(0,1,2,3,6)96. Master’s Thesis. Variable credit, but not more than six term hours in a single term, and not more than four in each summer term. Registration in several sections may be needed to obtain the desired number of thesis hours. For example, four term hours of thesis would require registration in EMIS 7396 and 7196.
8(0,1,2,3,6)90. Dissertation. Variable credit, but nor more than 15 term hours in a single term and not more than 10 term hours in the summer terms. Registration in several sections may be needed to obtain the desired number of dissertation hours. For example, 12 term hours of dissertation would require registration in EMIS 8390 and 8990.