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| Decision Sciences and Engineering Systems (School of Engineering) |
| DSES-2010 Statistics for Management Descriptive statistics, probability and random variables, point and interval estimation, hypothesis testing, sample size determination, contingency table analysis, basic experimental design and analysis of variance, simple linear regression. Use of statistical software on business datasets. Students cannot obtain credit for both this course and ENGR-2600. Prerequisite: MATH- 1010. Fall term annually. 4 credit hours |
| DSES-2200 Production and Operations Management for Industrial Engineers The analysis and design of production systems in manufacturing and service industries. Topics include forecasting, scheduling, inventory systems, total quality management, work load balancing, and capacity planning. Microcomputer software is used extensively. Students cannot obtain credit for both this course and DSES-2210. Prerequisite: MATH-1020 or equivalent. Spring term annually. 3 credit hours |
| DSES-2210 Production and Operations Management and Cost Accounting The design and analysis of production and service systems. Topics include forecasting, scheduling, inventory systems, total quality management, line balancing, and capacity planning. Introduction to cost accounting. Use of analytic techniques in accounting-based decision making. Formulation and solution of POM models practiced on computers. Students cannot obtain credit for both this course and ENGR-4700 or DSES-2200. Prerequisites: MATH-1020 or equivalent. Spring term annually. 4 credit hours |
| DSES-2940 Readings in DSES 1 to 4 credit hours |
| DSES-2960 Topics in DSES 4 credit hours |
| DSES-4140 Statistical Analysis Review of simple and multiple regression, selection procedures, regression diagnostics, residual analysis, stepwise regression, analysis of variance, design of experiments including factorial experiments, analysis of ordinal data and nonparametric inference, basic time series models. Extensive use of statistical software. Emphasis on statistical applications to industrial engineering. Prerequisites: ENGR-2600 and knowledge of calculus. Fall term annually. 4 credit hours |
| DSES-4200 Design and Analysis of Work Systems Analysis and design of work and workplace.Topics covered include human-machine systems, ergonomics, work measurement systems, methods and standards, process design, direct time study, standard time data, predetermined time systems, work sampling, work load balancing, and workplace layout. Computer-based analysis of problems in work systems. Prerequisite: ENGR-2600 or equivalent. Fall term annually. 3 credit hours |
| DSES-4230 Quality Control The statistical approach to manufacturing quality control is emphasized. Consideration is given to the managerial implications and responsibilities in implementing the statistical approach. Topical coverage includes construction and interpretation of various control charts; special control charts (e.g., CUSUM, EWMA); graphical methods; specifications, tolerance limits, process capability indices; acceptance sampling; discussion of experimental design; and Taguchi methods of quality improvement. Prerequisites: DSES-4140 or DSES-4760 (MATP-4620). Spring term annually. 3 credit hours |
| DSES-4240 Engineering Project Management Planning, controlling, and evaluating engineering projects. Use of network analysis techniques, PERT/CPM, budget control, time/cost tradeoff, time estimation, resource allocation, and resource leveling. Extensions include probabilistic models, multiple resource models, project organization, risk analysis, technical forecasting, and network theory. Students cannot obtain credit for both this course and ENGR-4750. Fall term annually. 3 credit hours |
| DSES-4250 Facilities Design and Industrial Logistics An in-depth study of the major design issues in location and physical configuration of production and service facilities. The course emphasizes the use of mathematical models, computer modeling, and quantitative analysis as aids to the design process. Topics include plant layout and location, material handling, material flow analysis, and distribution systems. Major course concepts are developed through case studies and projects. Prerequisites: DSES-2200 or equivalent, DSES-4140 or equivalent, and DSES-4640 or DSES-4770 (MATP-4700) or equivalent. Spring term annually. 3 credit hours |
| DSES-4260 Industrial Safety and Hygiene Survey of procedures and practices in industrial safety and hygiene including government regulation (OSHA), life safety, electrical safety, air contamination, noise, radiation, ventilation, illumination, toxicology, and safety engineering organization. Contemporary topics (asbestos, PCBs, AIDS) are also covered. Fall term annually. 3 credit hours |
| DSES-4270 Industrial and Management Engineering Design This course provides a capstone and professional experience. Student teams work on independent projects in any field of industrial and management engineering approved by a faculty adviser. Typically, projects involve a manufacturing and service sector client who provides the student with an opportunity to gain an actual industrial experience. Memos, progress reports, and a final written and oral report are submitted to the project adviser and client. This course is a writing-intensive course. Prerequisite: senior standing. Fall and spring terms annually. 3 credit hours |
| DSES-4280 Decision Focused Systems Engineering The objective of this course is to introduce students to systems engineering, especially from a decision focused perspective. Systems concepts, methodologies, models and tolls are covered in relation to a system’s design, development, test, evaluation, and operation. Decisions concerning a system’s reliability, maintainability, product ability, disposability, and affordability are systematically considered. A range of systems, including service systems, is also considered. Spring annually pre- or co-requisite ENGR 2600. 3 credit hours |
| DSES-4470 Corporate Strategic Planning and Modeling The integration of quantitative modeling concepts from management science, statistics, and industrial engineering as applied to strategic planning and corporate modeling. Emphasis on analytical application utilizing personal computers. Individual and group projects are utilized to provide experience in developing and managing complex planning and modeling projects. Prerequisites: DSES-4140 or equivalent and DSES-4650. Spring term annually. 3 credit hours |
| DSES-4510 Information Systems I This course surveys information-systems technology for the management of corporate information as a resource. Topics include elements of system design life cycle, database concepts, and Internet processing. Managerial and technical dimensions of information systems are blended in a framework of MIS. Projects are required. Prerequisite: CSCI-1100 or equivalent. Spring term annually. 3 credit hours |
| DSES-4520 Information Systems II: System Analysis and Database Design This course reviews information engineering methods and techniques in information system analysis and enterprise database design. Related topics such as telecommunications and enterprise integration and modeling are also discussed. The impact of advances in information technology is presented in the context of enterprise planning. Projects are required. Prerequisite: DSES-4510 or equivalent. Spring term annually. 3 credit hours |
| DSES-4530 Information Systems This course surveys information-systems technology for the management of enterprise information as a resource. Topics include elements of system design life cycle, database concepts, and decision support. Managerial and technical dimensions of information systems are blended in a framework for IS systems. Additional topics include telecommunications, artificial intelligence (including expert systems), and structured design. The implementation, operation, and maintenance of information systems are also discussed. Projects are required. Students cannot obtain credit for both this course and DSES-4510 or DSES-4520. Prerequisite: CSCI-1100 or equivalent. Fall term annually. 4 credit hours |
| DSES-4610 Operations Research Methods I Development of basic approaches of deterministic operations research to decision problems. Focus on optimization algorithms. Introduction to linear, integer, binary integer and nonlinear programming. Genetic algorithms. Consideration of model formulation and implementation. Prerequisite: MATH-1020 or equivalent. Fall term annually. 3 credit hours |
| DSES-4620 Operations Research Methods II Development of basic approaches of probabilistic operations research to decision problems. Focus on the formulation, estimation, and analysis of Markov, queuing, and discrete-event simulation models. Extensive use of computers. Prerequisite: DSES-4140 or equivalent. Spring term annually. 3 credit hours |
| DSES-4640 Operations Research I Introduction to modeling and linear programming (LP) formulations of decision problems. Development of algorithms for deterministic LP models including general LP models and network models. Introduction to goal programming, dynamic programming, integer programming and nonlinear programming. Formulation and solution of LP models practiced using spreadsheet software or other LP software tools. Students cannot obtain credit for both this course and DSES-4610 or DSES-4770 or MATP-4700. Prerequisites: MATH-1020 or equivalent. Fall term annually. 4 credit hours |
| DSES-4650 Operations Research II Development of basic approaches of probabilistic operations research to decision problems using Markov, queuing, and discrete-event simulation models. Focus on the formulation, estimation, and analysis of stochastic models. Extensive use of computer-based modeling. Students cannot obtain credit for both this course and DSES-4620. Prerequisite: ENGR-2600 or equivalent. Spring term annually. 4 credit hours |
| DSES-4750 Probability Theory and Applications Axioms of probability, joint and conditional probability, random variables, probability density and distribution functions, expectation, functions of random variables, and limit theorems. Applications of probability to models in operations research, including queuing theory and Markov chains. (Cross listed as MATP-4600. Students cannot obtain credit for both this course and MATP-4600.) Prerequisites: MATH-1020 or equivalent or permission of instructor. Fall term annually. 4 credit hours |
| DSES-4760 Mathematical Statistics A course in the theory of statistics which will provide students with a basic foundation for more specialized statistical methodology courses. Topics include sampling and sampling distributions; point estimation including method of moments, maximum likelihood estimation, uniform minimum variance estimation and properties of the associated estimators; confidence intervals; hypothesis testing including uniformly most powerful, likelihood ratio approaches, chi-square tests for goodness-of-fit and independence. The course will conclude with an introduction to linear statistical models. (Cross listed as MATP-4620. Students cannot obtain credit for both this course and MATP-4620.) Prerequisite: DSES-4750 or MATP-4600 or equivalent calculus-based course. Spring term annually. 4 credit hours |
| DSES-4770 Mathematical Models of Operations Research Introduction to deterministic models of operations research including linear programming formulations, the simplex algorithm, degeneracy, geometry of convex polyhedra, duality theory, and sensitivity analysis. Special linear programming models for assignment, transportation, and network problems. Integer programming formulations along with branch and bound solution. Dynamic programming. (Cross listed as MATP-4700. Students cannot obtain credit both for this course and MATP-4700.) Prerequisites: MATH-1020 and MATH-2010 or ENGR-1100 or equivalent, or permission of instructor. Fall term annually. 4 credit hours |
| DSES-4780 Computational Optimization An introduction to nonlinear programming. Models, methods, algorithms, and computer techniques for nonlinear optimization are studied. Students investigate contemporary optimization methods both by implementing these methods and through experimentation with commercial software. Nonmajors wishing to gain practical optimization skills are welcome in this course. A course project allows students to explore optimization methods and practical problems directly related to their interests. (Cross listed as MATP-4820. Students cannot obtain credit for both this course and MATP-4820.) Prerequisites: MATP-4700 or DSES- 4770, and MATH-2010 or ENGR-1100, and CSCI-1100, or equivalent, or permission of instructor. Spring term annually. 4 credit hours |
| DSES-4810 Computational Intelligence With ever-increasing computer power readily available, new engineering methods based on “soft computing” are emerging at a rapid rate. This course provides students a working knowledge in computational intelligence covering the basics of fuzzy logic, neural networks, genetic algorithms, simulated annealing, wavelet analysis, fractal structures, and chaotic time series analysis. Applications in control, optimization, data mining, fractal image compression, and time series analysis are illustrated with engineering case studies. Spring term annually. 3 credit hours |
| DSES-4940 Readings in DSES 1 to 6 credit hours |
| DSES-4960 Topics in DSES 3 credit hours |
| DSES-4980 Senior Design Project 1 to 4 credit hours |
| DSES-6010 Applied Regression Analysis Emphasis is on empirical model building and evaluation for both multiple linear and nonlinear regression models. Topics specifically addressed are simultaneous estimation, diagnostics and remedial measures, selection procedures, locally weighted least squares classification variables, binary response variables, time series data, nonlinear estimation, software packages. Prerequisite: DSES-4140, or DSES-4760 (MATP-4620), or DSES-6110, or permission of the instructor. Fall term annually. 3 credit hours |
| DSES-6020 Design of Experiments Methods of designing experiments so that statistical analysis of the resulting data will yield the maximum useful information. Testing of hypotheses; analysis of variance and covariance. Various designs, including the factorial and its modifications, incomplete blocks, Latin squares, and response surface designs are covered. Also discussed are optimality properties of design. Prerequisites: DSES-4140, or DSES-4750 (MATP-4600) and DSES-4760 (MATP-4620), or DSES-6110, or permission of the instructor. Spring term annually. 3 credit hours |
| DSES-6030 Sampling Methods Sampling procedures including the following specific techniques: simple, stratified, systematic, cluster, double, and multiple sampling; estimates for totals, proportions, and variances; ratio and regression estimates; sources of error in surveys. Prerequisite: DSES-4140 or DSES-6110 or equivalent. Offered on sufficient demand. 3 credit hours |
| DSES-6040 Nonparametric Methods Distribution-free methodology, order statistics, quantiles, runs tests, rank tests, one-sample and two-sample location and scale problems, k-sample problems, goodness-of-fit tests, measures of association, asymptotic efficiencies. Nonparametric estimation. Prerequisite: DSES-4760 (MATP-4620) or DSES-6110, or equivalent. Offered on sufficient demand. 3 credit hours |
| DSES-6050 Stochastic Processes A foundational course to introduce the theory of stochastic processes and how it is used to mathematically model a wide variety of empirical phenomena such as queuing systems, inventory control, telecommunications and data networks, and reliability and maintainability. Topics include review of probability, random variables, and conditional expectation; definition of various classes of stochastic processes and their properties; the homogeneous, nonhomogeneous, and compound Poisson processes; renewal processes, discrete and continuous parameter Markov chains, birth and death processes. Prerequisites: calculus, DSES-4750 (MATP-4600). Corequisite: DSES-4760 (MATP-4620). Spring term even-numbered years. 3 credit hours |
| DSES-6060 Applied Multivariate Analysis Multivariate distributions; correlations, multiple and partial; estimation and testing in multivariate analysis; multivariate regression analysis including regression with two or more variables subject to error; discriminating between multivariate populations; classification problems; determining the structure of multivariate observations by principle components and factor analysis. Prerequisites: DSES-4140 or DSES-6110. Spring term annually. 3 credit hours |
| DSES-6070 Statistical Methods for Reliability Engineering Statistical methods for the analysis of life-test, failure, or other durational data. Engineering applications are emphasized, but the methods are applicable to biometric, actuarial, and social science durational data. Included are basic reliability concepts and definitions; statistical life and failure distributions such as the exponential, gamma, Weibull, normal, lognormal, and extreme value; probability and hazard plotting techniques; maximum likelihood and other estimation methods. Prerequisites: DSES-4140, or DSES-4760 (MATP-4620), or DSES-6110. Spring term odd-numbered years. 3 credit hours |
| DSES-6090 Decision Analysis Normative and behavioral views are taken of decision making under uncertainty. This includes a discussion of utility theory and the general problem of ascertaining decision makers’ preferences. Problem structuring techniques such as influence diagrams and knowledge maps are presented. Risk analysis, including risk assessment and management, is discussed. Decision analysis software is used. A class project in risk analysis is conducted. Prerequisites: DSES-6110 or equivalent and DSES-6500 or equivalent. Spring term odd-numbered years. 3 credit hours |
| DSES-6100 Time Series Analysis Study of time series data for both description and prediction. Main emphasis on the classical Box-Jenkins approach to model identification, estimation, and diagnosis. Includes an introduction to spectral analysis. Applications to real data series, including forecasting problems and empirical comparison of alternative approaches. Use of computer packages for time series analysis. Prerequisite: DSES-4760 (MATP-4620) or equivalent. Spring term odd-numbered years. 3 credit hours |
| DSES-6110 Introduction to Applied Statistics A graduate course in basic statistics. Stresses application to common tasks such as summarizing large databases, making quick estimates, establishing relationships among variables, forecasting, and evaluating alternatives. Topics include probability, common discrete and continuous distributions, sampling, confidence intervals, hypothesis tests, contingency tables, statistical process control, multiple regression analysis. Extensive use of computers to analyze data sets. Students cannot obtain credit for both this course and DSES-4140. Spring term annually. 3 credit hours |
| DSES-6130 Statistical Computing A course on modern computational and graphical statistics. It covers topics that are currently active in real world applications including biotechnology and information technology. The topics include stochastic simulation, importance sampling, Gibbs sampling, data visualization, dimensionality reduction, model selection, data smoothing techniques, and methods for pattern recognition. Prerequisites: DSES-4140 or DSES-4760 (MATP-4620), or DSES-6110. Fall term annually. 3 credit hours |
| DSES-6140 Exploratory Data Analysis Exposition of the philosophy and tools of exploratory data analysis. Tools include graphical techniques, data transformation, robust and resistant summaries, residual analysis, and resampling methods. Applications to the analysis of real data sets, stressing alternative analysis using statistical software. Prerequisites: DSES-4750 (MATP-4600) and DSES-4760 (MATP-4620) or equivalent; DSES-6100 recommended. Spring term even-numbered years. 3 credit hours |
| DSES-6150 Advanced Probability for Statistical Inference Discusses advanced probability concepts and their application to statistical inference. Topics include discrete and continuous distributions, moment generating functions, random vectors and joint distributions, order statistics, bivariate normal distribution, modes of convergence, central limit theorem, goodness of fit, and simulation of random variables. Prerequisites: DSES-4750 (MATP-4600) and DSES-4760 (MATP-4620) or permission of instructor. Fall term annually. 3 credit hours |
| DSES-6170 Management of Quality Processes and Reliability Definitions; corporate, economic, and government environments; international considerations; business processes and physical processes in manufacturing and services; control and enhancement of processes; organizing for and effecting change; experimental design for design and change; information systems; Deming approach; product and processes development; capital investment; empowerment of workers; people make it happen. Fall term annually. 3 credit hours |
| DSES-6180 Knowledge Discovery with Data Mining Data mining is the computationally intelligent extraction of information form large databases. It is the process of automated presentation of patterns, rules, and functions from large data bases to make crucial business decisions. This course takes a multi-disciplinary approach to data mining and knowledge discovery involving statistics, rule and tree induction, neural networks, genetic algorithms, visualization and fuzzy logic. The course is project driven and puts a special emphasis on the use of computational intelligence for scientific data mining related to drug design and bioinformatics. Prerequisite: ENGR-2600 or equivalent introductory course in statistics. Spring term annually. 3 credit hours |
| DSES-6200 Models in Facilities Planning and Materials Handling Analytical and computational modeling of industrial engineering problems in the areas of industrial and manufacturing logistics. Specific applications include facilities planning/design, materials handling equipment/systems, material storage/distribution systems, flow line scheduling and modeling. Prerequisites: DSES-4770 (MATP-4700) or DSES-4640 or equivalent, and DSES-6110 or equivalent. Fall term even-numbered years. 3 credit hours |
| DSES-6210 Theory of Production Scheduling Problems of scheduling several tasks over time.Topics include measures of performance, single machine sequencing, flowshop scheduling, the job shop problem, and priority dispatching. Integer programming, dynamic programming, and heuristic approaches to various problems are also presented. Prerequisites: DSES-4770 (MATP-4700), or equivalent. Fall term odd-numbered years. 3 credit hours |
| DSES-6220 Concurrent Engineering This course examines issues in concurrent engineering (CE), a product design process using extensive information and knowledge about the product’s manufacture and life cycle performance, including design for manufacturing and assembly. Spring term annually. 3 credit hours |
| DSES-6230 Quality Control and Reliability This course has the same content and requirements as DSES-4230 with material added. Additional topics include basic concepts of system and component reliability; statistical distributions such as the exponential, gamma, Weibull, and lognormal, important in the description of life and failure phenomena; and the graphical and quantitative analysis of complete and censored life-testing and failure data. Prerequisite: DSES-4140 or DSES-4760 (MATP-4620), or DSES-6110. Fall term annually. 3 credit hours |
| DSES-6470 Global Strategic Management of Technological Innovation The course helps develop an understanding of and the method for managing technology as a strategic resource of the firm. In doing so, an understanding of the process, roles, and rewards of technological innovation are developed. Integrating the strategic relationship of technology with strategic planning, marketing, finance, engineering, and manufacturing are covered. Governmental, societal, and international issues are briefly covered. The course uses a variety of cases, readings, reports, and lectures. (Cross listed as MGMT-6610. Students cannot obtain credit for both this course and MGMT-6610.) Prerequisite: permission of instructor. Spring term annually. 3 credit hours |
| DSES-6480 Service Operations Management This course discusses the role of services in an economy, managing services for competitive advantage, structuring the service enterprise, managing service operations, service productivity, quality, and growth. The final part concerns quantitative models with service operations. (Cross listed as MGMT-6480. Students cannot obtain credit for both this course and MGMT-6480.) Prerequisite: permission of instructor. Fall term annually. 3 credit hours |
| DSES-6500 Information and Decision Technologies for Industrial and Service Systems This course emphasizes topics related to information systems and decision making including information and decision systems in organizations, database systems, knowledge systems, system analysis and design, networks and telecommunications in information systems, information systems for service delivery. Fall term annually. 3 credit hours |
| DSES-6520 Enterprise Database Systems Focus on developing competence for database systems analysis, design and processing. Additional topics such as data and rules modeling, integrity, data languages, DBMS, and distributed databases are also covered. The course presents a high-level look at design and operation issues from the perspective of information systems. Projects are required. Prerequisite: DSES-6500 or permission of instructor. Spring term annually. 3 credit hours |
| DSES-6530 Decision Support and Expert Systems Concepts and types of managerial decision support systems. Topics include models for decision making, applied database, and applications of artificial intelligence. Knowledge representation, knowledge acquisition, and the development of expert systems are taught through cases and a project. Use of commercially available software packages. Prerequisite: DSES-4530 or DSES-6500 or permission of instructor. Spring term annually. 3 credit hours |
| DSES-6550 Information Systems Analysis and Design Methods and procedures for understanding and modeling an organization’s existing and planned information processing activities (both computerized and manual) are presented and analyzed. These models are then used to develop and design new information processing systems and management information systems. The design process includes procedures for implementing systems successfully. A CASE technology is utilized in conjunction with the design process. Prerequisite: DSES-6500 or permission of instructor. Offered on sufficient demand. 3 credit hours |
| DSES-6560 Information Management in Manufacturing Systems Role of information systems in manufacturing; conventional information handling methods, such as CAD/CAM, the latest CIM, and the emerging concepts and techniques of information integration. A systems development framework is employed, ranging from strategic use of information systems technology for planning, to manufacturing information systems analysis and design. Term projects required. Fall term annually. 3 credit hours |
| DSES-6570 Information Technology and Systems for E-Business E-business uses Internet and other new information technologies to bring about extended enterprises on a global scale. The course examines the underlying models, methods, and the techniques of E-business systems from this enterprise perspective. Web technologies, information systems engineering, and contemporary topics such as agents and scalable enterprises are covered. Laboratory assignments and term projects are required. Prerequisites: Information technology literacy. Spring term annually. 3 credit hours |
| DSES-6600 Models for Production Control and Service Logistics This course covers deterministic and stochastic models applied in manufacturing and service organizations with special emphasis on the study of inventory control models, logistics management models, and queuing models. Analysis of these models and their application to design and planning problems in manufacturing as well as service systems is emphasized. Prerequisites: DSES-4640 or DSES-4770 (MATP-4700), and DSES-6110 (or equivalent), or permission of instructor. Spring term annually. 3 credit hours |
| DSES-6610 Applied Operations Research An introduction to the application of deterministic and stochastic operations research. Students will learn how to apply common optimization methods to the point of formulation and computer solution. Case studies and examples are solved using a microcomputer solutions package. Prerequisite: DSES-6110 or permission of instructor. Spring term annually. 3 credit hours |
| DSES-6620 Discrete-Event Simulation A thorough development of a simulation language is stressed in order to progress through a series of increasingly sophisticated applications of computer simulation. Projects cover a wide range of topics: production systems, inventory, finance, transportation, and public systems. The course includes model development, statistical analysis of simulation input/output data, validation planning, and managing simulation projects. Prerequisite: DSES-6110 or equivalent. Fall term annually. 3 credit hours |
| DSES-6630 Continuous and Stochastic System Simulation An advanced course in simulation. Covers aspects of modeling large-scale systems via simulation environments such as ARENA and PROMODEL and analysis via statistical techniques and animation. Extensive use of case studies and team exercises. Prerequisite: DSES-6620 or permission of instructor. Spring term annually. 3 credit hours |
| DSES-6640 Quantitative Analysis of Health Systems Analytical and computer-based approaches to problems involving health care organizations are presented. Topics such as productivity, improvement, reengineering, total quality management, models to improve utilization of scarce resources, and spreadsheet models are included. The course puts analytical approaches into practice through a “live case study” in cooperation with a regional health organization. Prerequisite: DSES-6610 or equivalent. Offered on sufficient demand 3 credit hours |
| DSES-6760 Combinatorial Optimization and Integer Programming Review of exact and heuristic methods for solving discrete problems, including the traveling salesman problem, the knapsack problem, packing and covering problems. Algorithm complexity and NP-completeness, cutting plane methods and polyhedral theory, branch and bound, simulated annealing, tabu search, Lagrangian duality. (Cross listed as MATP-6620. Students cannot obtain credit for both this course and MATP-6620.) Prerequisites: DSES-4770 (MATP-4700). Spring term odd-numbered years. 4 credit hours |
| DSES-6770 Linear Programming A unified development of linear systems and linear programming, polyhedral theory, the simplex method, interior point methods, decomposition methods for large scale linear programming problems, the ellipsoid method, column generation algorithms for stochastic programming and other problems. (Cross listed as MATP-6640. Students cannot obtain credit for both this course and MATP-6640.) Prerequisites: DSES-4770 (MATP-4700). Spring term even-numbered years. 4 credit hours |
| DSES-6780 Nonlinear Programming Convex sets and functions, optimality conditions in nonlinear programming, Lagrangian duality, quadratic programming algorithms for nonlinear programming including Newton’s method, quasi-Newton methods, conjugate gradient methods, together with proofs of convergence. (Cross listed as MATP-6600. Students cannot obtain credit for both this course and MATP-6600.) Prerequisites: MATH-4200 or equivalent, or permission of instructor. Fall term annually. 4 credit hours |
| DSES-6820 Queuing Systems and Applications A course on fundamentals of stochastic processes and queuing theory emphasizing applications. Poisson processes, renewal processes, Markov chains, general methods in the study of Markovian and non-Markovian systems, tandem queues, networks of queues, priority and bulk queues, computational methods and simulation. Focus of the course is the application of these tools in the performance evaluation and design of computer systems, communication networks, manufacturing systems, and service systems. (Cross listed as ECSE-6820. Students cannot obtain credit for both this course and ECSE-6820.) Prerequisite: ECSE-4500 or DSES-4750 (MATP-4600), or equivalent. Spring term annually. 3 credit hours |
| DSES-6830 Large-Scale Systems: Case Studies and Analyses A case-study approach introducing the systems method to analyze large-scale systems. Qualitative and quantitative study of the problems, from problem examination to problem definition, to problem solution, and to implementation. Case studies in manufacturing, transportation, community development, water resources, and criminal justice. Emphasis is on analysis of real-world problems using techniques of systems engineering and operations research and considering diverse factors such as economic, technical, sociological, and environmental issues. (Cross listed as ECSE-6830. Students cannot obtain credit for both this course and ECSE-6830.) Prerequisite: ECSE-4500. Corequisite: DSES-4770 (MATP-4700) or equivalent or permission of instructor. Fall term odd-numbered years. 3 credit hours |
| DSES-6840 Modeling Large-Scale Systems Applications of operations research and systems analysis techniques to mathematical modeling of complex systems, especially large-scale public systems. Discussion of model-building approaches, emphasizing the role of creativity, rationality, and mathematics. Introduction of important quantitative techniques (e.g., geometrical probability, optimization theory, and stochastic processes) and their application to modeling emergency service systems, spatial distribution of public service facilities, congestion, land-use patterns, transportation systems, demographics, and energy. (Cross listed as ECSE-6840. Students cannot obtain credit for both this course and ECSE-6840.) Prerequisites: DSES-4770 (MATP-4700) and ECSE-4500 or equivalent; DSES-6830 (ECSE-6830) desirable. Fall term annually. 3 credit hours |
| DSES-6860 Evaluation Methods for Decision Making Evaluation provides structured information for policy-relevant decision making, based on a purposeful analysis of the identified measures. Topics include tests of hypotheses, randomization/control schemes, measures framework, measurement methods, and pertinent analytic techniques. Emphasis is on the application of evaluation methods (including systems engineering and operations research techniques) to issues arising in criminal justice, education, health, housing, transportation, welfare, automated information systems, and military programs. (Cross listed as ECSE-6860. Students cannot obtain credit for both this course and ECSE-6860.) Prerequisite: ECSE-4500 or DSES-4750 (MATP-4600) or equivalent. Fall term odd-numbered years. 3 credit hours |
| DSES-6870 Introduction to Neural Networks Neural networks are program and memory at once, useful where traditional techniques fail, i.e., for artificial speech and image recognition. Emphasis on existing and emerging engineering applications. Parallel distributed processing, Hebb’s rule, Hopfield net, back-propagation algorithm, perceptrons, unsupervised learning, Kohenen self-organizing map, genetic algorithms, neocognitron, adaline. Illustrated with computer programs and lectures. (Cross listed as ENVE-6680. Students cannot obtain credit for both this course and ENVE-6680.) Fall term odd-numbered years. 3 credit hours |
| DSES-6890 Multiple Criteria Decision Making Consideration of multiple objectives under certain and uncertain conditions, the concept of the ideal, anti-ideal, and value tradeoffs, the decision-making process, measurement of attribute importance, linear multi-objective programming, goal programming, compromise programming, dealing with uncertainty. Prerequisites: DSES-4770 (MATP-4700) or equivalent, and DSES-6110 or equivalent. Spring term odd-numbered years. 3 credit hours |
| DSES-6900 Seminar in DSES Research A review of active DSES doctoral research projects and activities. Discussion of the process and stages of doctoral research in DSES. Communication of scientific research results. Prerequisite: DSES doctoral student or permission of instructor. Fall term annually. 0 credit hours |
| DSES-6910 Advanced Seminar in DSES A writing intensive course. Students develop research papers under the guidance of a selected faculty adviser and present research findings in class. It is anticipated that the research paper will lead to identification of the broad area of dissertation research. Prerequisite: DSES doctoral student or permission of instructor. Corequisite: Having previously passed the DSES DQE or applied to take it in the current semester. Fall term annually. 2 credit hours |
| DSES-6940 Readings in DSES 3 to 6 credit hours |
| DSES-6960 Topics in DSES 3 credit hours |
| DSES-6980 Master’s Project Active participation in a master’s-level project under the supervision of a faculty adviser, leading to a master’s project report. Grades of IP are assigned until the master’s project has been approved by the faculty adviser. If recommended by the adviser, the master’s project may be accepted by the Office of Graduate Education to be archived in the Library. Grades will then be listed as S. 1 to 9 credit hours |
| DSES-6990 Master’s Thesis Active participation in research, under the supervision of a faculty adviser, leading to a master’s thesis. Grades of IP are assigned until the thesis has been approved by the faculty adviser and accepted by the Office of Graduate Education to be archived in a standard format in the library. Grades will then be listed as S. 1 to 9 credit hours |
| DSES-9990 Dissertation Active participation in research, under the supervision of a faculty adviser, leading to a doctoral dissertation. Grades of IP are assigned until the dissertation has been publicly defended, approved by the doctoral committee, and accepted by the Office of Graduate Education to be archived in a standard format in the library. Grades will then be listed as S. Variable credit hours |
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