Academics

Masters Degree

Ph.D. Degree

Ph.D. Minor in Operations Research

Coursework

Operations Research Courses

Participating Programs

Masters Degree

The prerequisites for admission to the M.S., M.A., M.Eng. dual-title degree programs in Operations Research, in addition to those prescribed by the graduate major program, include the following or their equivalent: MATH 140 or 141 or 220; CMPSC 101 or 201 or 203; and 3 credits of probability and statistics. Students who have not completed courses substantially equivalent to any of these courses should plan to include such prerequisite courses in their program of study.

To qualify for a dual-title degree after admission to the Operations Research Program, students must satisfy the requirements of the graduate major program in which they are registered, in addition to the minimum requirements, or their equivalent, in the Operations Research Program. Students must also enroll in OR 590 - OR Colloquium, for at least 1 credit in each year enrolled in the program and in residence. The maximum number of OR 590 credits required for an M.A., M.S., or M. Eng. student is 2.

For the M.S. or M.A dual-title degree in Operations Research, a minimum of 18 credits are required These credits are selected from specific program areas and the minimum requirements are: 6 credits in Stochastic/Statistical Methods including a minimum of 3 credits in each of the areas of statistical methods and stochastic processes; 6 credits in Optimization including a minimum of 3 credits in linear programming; 3 credits in Computational Methods; and 3 credits in Applications/Specialization (Application courses are those that involve problem solving through the use of decision methods.) Of these 18 credits, a minimum of 9 credits must be in the 500 series. Particular courses may satisfy both the graduate major program requirements and those in the Operations Research program.

If a thesis is required, the supervisor must be a member of the graduate faculty recommended by the chair of the program granting the degree and approved by the Operations Research Committee as qualified to supervise thesis work in operations research. A paper or report may be written in lieu of the M.S. or M.A. thesis upon approval of the student's graduate major program. An M.Eng. student or a student selecting the paper or report option must take an additional 6 credits in the Operations Research Program. It is the prerogative of the graduate major program to assign these credits to one or more of the following categories: stochastic/statistical methods, optimization, computational methods, or applications.

The Masters student will have a committee of at least two members, one of which must be from outside the student's graduate major program and a member of the Operations Research Faculty or approved by the Operations Research Committee Chair.

Ph.D. Degree

For the Ph.D. dual-title degree in Operations Research, in addition to those prescribed by the graduate major program, prerequisites for acceptance to the program without deficiency include the following or their equivalent: MATH 401 or 436; CMPSC 101 or 201 or 203; and 3 credits of probability and statistics. Students who have not completed courses substantially equivalent to any of these courses should plan to include such prerequisite courses in their program of study.

To qualify for a dual-title degree in Operations Research after admission to the operations Research Program, students must satisty the requirements of the graduate major program in which they are registered, in addition to the minimum requirements, or their equivalent, in the Operations Research Program. Students must also enroll in OR 590 - OR Colloquium. for at least 1 credit in each year enrolled in the program and in residence.The maximum number of OR 590 credits required for a Ph.D dual title student is 4.

The minimum requirements for the Ph.D. dual-title degree in Operations Research are: 9 credits in Stochastic/Statistical Methods including a minimum of 3 credits in each of the areas of statistical methods and stochastic processes; 9 credits in Optimization including a minimum of 3 credits in linear programming; 6 credits in Computational Methods including a minimum of 3 credits in simulation; and 12 credits in Application s/Specialization. Of these 36 credits, a minimum of 18 credits must be in the 500 series, and particular courses may satisfy both the graduate major program requirements and those in the Operations Research Program.

The doctoral committee for a Ph.D. dual-title degree student is recommended by the graduate major program granting the degree. The chair and at least two members of a doctoral committee must be members of the graduate faculty and approved by the Operations Research Committee as qualified to supervise doctoral theses in operations research.

Ph.D. Minor in Operations Research

A Ph.D. minor program in Operations Research is available for doctoral students in graduate programs who find it advantageous to include advanced quantitative methods of systems analysis in their program of study and have been approved to do so by their doctoral committee. To qualify for a minor in Operations Research, students must satisfy the requirements of their graduate major programs, meet the same prerequisites as the M.S. dual-title degree, and meet the following minimum requirements: 6 credits in Stochastic/Statistical Methods including a minimum of 3 credits in each of the areas of statistical methods and stochastic processes; 6 credits in Optimization; and 3 credits in Computational Methods. A minimum of 6 must be taken in the 500 series. Students must also enroll in OR 590 - OR Colloquium, for at least 1 credit in each year enrolled in the program and in residence. The maximum number of OR 590 credits required for a Ph.D. minor student is 4.

The doctoral committee for a student seeking a minor in Operations Research must have at least one member approved by the Operations Research Committee.

Coursework

Courses of a like nature identified as the core of the program option have been given generic names and descriptions Each such listing may be satisfied by one of the courses given under it. The detailed requirements of each individual program are outlined in the application forms.

STOCHASTIC METHODS/STATISTICAL METHODS

Statistical Methods MATH/STAT 414, 415, 418 IE 511, 583, 584 SC&IS 535 STAT 460, 501, 502, 503 ECON 501 AEREC/ECON 510, 511

Stochastic Processes IE/SC&IS 516 MATH/STAT 416, 516, 519 STAT 515

OPTIMIZATION

Linear Programming IE 405, BA 450, MATH 484 IE 505 AEREC 527	Nonlinear Programming IE 521 MATH 549
Integer Programming IE 510	Dynamic Programming IE/SC&IS 519
Mathematical Programming MATH/CSE 555 IE 468, 512, 520 SC&IS 525

COMPUTATIONAL METHODS

Numerical Methods MATH/CSE 451, 455, 456, MATH/CSE 550, 553

Simulation Methods IE 453, BA/OISM 455 IE 522, 540 SC&IS 545

OPEN AREAS - APPLICATIONS/SPECIALIZATION

Includes many of the above courses as well as courses in quality control, scheduling, inventory, queueing, decision analysis, game theory, logistics, expert systems, econometrics, forecasting, and others:

ABE 469W, 559; AEREC 501 ASM 429W; BA 427; CSE 460, 465, 565, 560, 555, 563, 564; ECON 521, EE 529 / EE 581; ERM 412; GEOG 425, 455,481, 580, 581; IE 402, 425, 454,  507, 509, 532, 554, 562, 566; MATH 485,486; MEM 510; MKTG 511,555; MNPR 520; PNG 430,512,514; STAT 510,540; SC&IS 505,510,520,530.

 

OPERATIONS RESEARCH COLLOQUIUM

OR 590 (1 credit)

 

Operations Research Courses

A B E 469W OPTIMIZATION OF BIOLOGICAL PRODUCTION AND PROCESSING SYSTEMS (3) Engineering and biological principles combined with economics and mathematical techniques to evaluate and optimize biological production and processing systems. Prerequisite: A B E 402 , A B E 403 , A B E 406

A B E 559 BIOLOGICAL AND AGRICULTURAL SYSTEMS SIMULATION ( 3) Effective Date: SP2006 Continuous simulation modeling of biological and physical systems, numerical simulation techniques, validation and verification, difference measures, sensitivity analysis. Prerequisite: MATH 111 or MATH 141

AEREC 501 (AG EC) AGRICULTURAL PRODUCTION ECONOMICS I ( 3) Application of microeconomic theory to problems and decisions of farm households and agricultural firms. Prerequisite: ECON 502

AEREC 510 (AG EC) ECONOMETRICS I ( 3) General linear model, multicolinearity, specification error, autocorrelation, heteroskedasticity, restricted least squares, functional form, dummy variables, limited dependent variables. Prerequisite: ECON 490 or STAT 462 or STAT 501

AEREC 511 (AG EC) ECONOMETRICS II ( 3) Stochastic regressors, distributed lag models, pooling cross-section and time- series data, simultaneous equation models. Prerequisite: AG EC 510

AEREC 527 (AG EC) QUANTITATIVE METHODS I ( 3) Quantitative techniques applied to agricultural economic issues. Prerequisite: ECON 502

AEREC 589 (AG EC) SEMINAR IN ECONOMETRIC THEORY ( 3) Theories and methods relevant to the application of statistical methods to economics. Prerequisite: AG EC 510 , AG EC 511

B A 427 RISK AND DECISIONS ( 3) Conceptualizing decisions involving risk, analyzing choices, estimating the risk, and communicating the analysis. Prerequisite: MATH 110 or MATH 140 and either MS&IS 200 or STAT 200

B A 450 OPTIMIZATION FOR BUSINESS DECISIONS ( 3) Optimization models quickly and efficiently analyze a large number of scenarios to find the best course of action for business applications. Prerequisite: MATH 110 or MATH 140 and either MS&IS 200 or STAT 200

B A 455 (OISM) SIMULATION MODELS OF BUSINESS PROCESSES ( 3) Building computer simulation models to understand business processes, and to test ideas about how they can be modified. Prerequisite: MATH 110 or MATH 140 and either MS&IS 200 or STAT 200

A S M 429W AGRICULTURAL SYSTEMS ANALYSIS AND MANAGEMENT ( 3) Theory of systems thinking; quantitative techniques for analysis and optimization; and qualitative approaches for agricultural decision-making processes. Prerequisite: MATH 110 , PHYS 250 , 12 credits of A S M courses, computer experience

CSE 431 INTRODUCTION TO COMPUTER ARCHITECTURE ( 3) Principles of computer architecture: memory hierarchies and design, I/O organization and design, CPU design and advanced processors. Prerequisite: CSE 331

CSE 441W INTRODUCTION TO DATABASE MANAGEMENT SYSTEMS ( 3) Database system concepts: file organizations and retrieval algorithms; the three data models (relational, hierarchical, and network) and their database implementations. Prerequisite: CSE 465 , ENGL 202C

CSE 460 COMBINATORICS AND GRAPH THEORY ( 3) An introduction to combinatorics and graph theory, with emphasis on applications and their organization for solution on digital computers. Prerequisite: CSE 465

CSE 465 DATA STRUCTURES AND ALGORITHMS ( 3) Fundamental concepts of computer science: data structures, analysis of algorithms, recursion, trees, sets, graphs, sorting. Prerequisite: CSE 260 or MATH 311W

CSE 481 INTRODUCTION TO ARTIFICIAL INTELLIGENCE I ( 3) Introduction to the theory, research paradigms, implementation techniques, and philosophies of artificial intelligence. Prerequisite: CSE 120

CSE 553 (MATH) INTRODUCTION TO APPROXIMATION THEORY ( 3) Interpolation; remainder theory; approximation of functions; error analysis; orthogonal polynomials; approximation of linear functionals; functional analysis applied to numerical analysis. Prerequisite: MATH 401 , 3 credits in Computer Science and Engineering

CSE 555 (MATH) NUMERICAL OPTIMIZATION TECHNIQUES ( 3) Unconstrained and constrained optimization methods, linear and quadratic programming, software issues, ellipsoid and Karmarkar's algorithm, global optimization, parallelism in optimization. Prerequisite: CSE 456

CSE 560 THEORY OF GRAPHS AND NETWORKS ( 3) Theory and applications of graphs, including structure of graphs, network analysis, and algorithms for computer solution of graph-theoretic problems. Prerequisite: CSE 565

CSE 562 PROBABILISTIC ALGORITHMS ( 3) Design and analysis of probabilistic algorithms, reliability problems, probabilistic complexity classes, lower bounds. Prerequisite: CSE 565

CSE 563 PARALLEL ALGORITHMS ( 3) Computational aspects of VLSI: synthesis/analysis of efficient parallel and distributed algorithms; computational structures; models of parallel computers and their interrelationships. Prerequisite: CSE 565

CSE 564 COMPLEXITY OF COMBINATORIAL PROBLEMS ( 3) NP-completeness theory; approximation and heuristic techniques; discrete scheduling; additional complexity classes. Prerequisite: CSE 565

CSE 565 ALGORITHM DESIGN AND ANALYSIS ( 3) An introduction to algorithmic design and analysis. Prerequisite: CSE 465 Concurrent: CSE 468

ECON 500 INTRODUCTION TO MATHEMATICAL ECONOMICS ( 3) Mathematical Economics: Applications of Mathematical Techniques to Economics.

ECON 501 ECONOMETRICS ( 3) Econometrics: Applications of Statistical Techniques to Economics

ECON 510 ECONOMETRICS I ( 3) General linear model, multicolinearity, specification error, autocorrelation, heteroskedasticity, restricted least squares, functional form, dummy variables, limited dependent variables. Prerequisite: ECON 501 or STAT 462 or STAT 501

ECON 511 ECONOMETRICS II ( 3) Stochastic regressors, distributed lag models, pooling cross-section and time- series data, simultaneous equation models. Prerequisite: ECON 510

ECON 521 ADVANCED MICROECONOMIC THEORY ( 3 - 6 per semester) Theory of consumer behavior; theory of the firm; price determination in product and factor markets; introduction to welfare economics.

ECON 589 SEMINAR IN ECONOMETRIC THEORY ( 3) Theories and methods relevant to the application of statistical methods to economics. Prerequisite: ECON 510 , ECON 511

E E 529/E E 581 OPTIMAL CONTROL ( 3) Variational methods in control system design; classical calculus of variations, dynamic programming, maximum principle; optimal digital control systems; state estimation. Prerequisite: E E 527

E R M 412 RESOURCE SYSTEMS ANALYSIS ( 3) The concept of systems; techniques of analysis, including input/output, mathematical programming, and simulation; application to resource systems. Prerequisite: BIOL 220W , E R M 151 , E R M 300 , and STAT 240 ; MATH 111 or MATH 141

GEOG 425 CARTOGRAPHIC INFORMATION SYSTEMS ( 3) Theory and methods for the application of computers to cartographic symbolization and design problems. Design of computer mapping packages. Prerequisite: GEOG 321 , GEOG 356

GEOG 455 SPATIAL ANALYSIS II ( 3) Normative and probabilistic models of spatial behavior; adaptive systems in geographic space; interaction and system stability. Prerequisite: GEOG 454

GEOG 481 GEOGRAPHIC INFORMATION SYSTEMS DESIGN AND EVALUATION ( 3) Design and evaluation of Geographic Information Systems and other forms of integrated spatial data systems. Prerequisite: GEOG 357

GEOG 580 SPATIAL DATA STRUCTURES AND ALGORITHMS ( 3) In-depth examination of geographic information system components; representation and storage of spatial data, spatial algorithms, input-output considerations. Students who have passed GEOG 480 may not schedule this course for credit. Prerequisite: GEOG 456 , GEOG 457

GEOG 581 GEOGRAPHIC INFORMATION SYSTEMS DESIGN AND EVALUATION ( 3) Graduate-level examination of Geographic Information System and other forms of integrated spatial data system design. Prerequisite: GEOG 580

I E 402 ADVANCED ENGINEERING ECONOMY ( 3) Concepts and techniques of analyses useful in evaluating engineering projects under deterministic and uncertain conditions. Prerequisite: I E 302 , I E 322 , I E 405

I E 468 OPTIMIZATION MODELING AND METHODS ( 3) Mathematical modeling of linear, integer, and nonlinear programming problems and computational methods for solving these classes of problems. Prerequisite: I E 405 , MATH 231

I E 540 MANUFACTURING SYSTEMS SIMULATION ( 3) Use of simulation in design and process improvement of manufacturing systems. Analysis of simulation language structure. Readings in current literature. Prerequisite: I E 453

I E 583 RESPONSE SURFACE METHODOLOGY AND PROCESS OPTIMIZATION ( 3) Response Surface Methodologies used for sequential experimentation and optimization of production processes. Statistical design and analysis of such experiments. Prerequisite: I E 511 or STAT 501

I E 584 TIME SERIES CONTROL AND PROCESS ADJUSTMENT ( 3) Design of Time Series-based process controllers for Quality Engineering. Study of the effect of autocorrelation on control chart performance. Prerequisite: I E 423

I E 405 LINEAR PROGRAMMING ( 3) An introduction to the theory and application of the simplex method in solving the linear programming and dual problem. Prerequisite: MATH 220

I E 425 INTRODUCTION TO OPERATIONS RESEARCH ( 3) Effective Date: SP2006 An introduction to the method and techniques of mathematical decision making, including inventory, replacement, allocation, and waiting line problems. Prerequisite: I E 322 Concurrent: I E 405

IE 432 INTRODUCTION TO RELIABILITY ENGINEERING

I E 453 SIMULATION MODELING FOR DECISION SUPPORT ( 3) Effective Date: SP2006 Introduction of concepts of simulation modeling and analysis, with application to manufacturing and production systems. Prerequisite: CMPSC 201C or CMPSC 201F ; I E 323 , I E 425

I E 454 APPLIED DECISION ANALYSIS ( 3) Theory and practice of decision analysis applied to engineering problems. Prerequisite: I E 322

I E 505 LINEAR PROGRAMMING ( 3) An accelerated treatment of the main theorems of linear programming and duality structures plus introduction to numerical and computational aspects of solving large-scale problems. Prerequisite: I E 405

I E 507 OPERATIONS RESEARCH: SCHEDULING MODELS ( 3) Scheduling models with simultaneous job arrival and probabilistic job arrival, network scheduling, and scheduling simulation techniques. Prerequisite: I E 425

I E 509 OPERATIONS RESEARCH: WAITING LINE MODELS ( 3) Waiting line models including models with infinite queues, finite queues, single and multiple servers under various priorities and disciplines. Prerequisite: I E 516

I E 510 INTEGER PROGRAMMING ( 3) Study of advanced topics in mathematical programming; emphasis on large-scale systems involving integer variables. Prerequisite: I E 405

I E 511 EXPERIMENTAL DESIGN IN ENGINEERING ( 3) Statistical design and analysis of experiments in engineering; experimental models and experimental designs using the analysis of variance. Prerequisite: I E 323

I E 512 GRAPH THEORY AND NETWORKS IN MANAGEMENT ( 3) Graph and network theory; application to problems of flows in networks, transportation and assignment problems, pert/CPM, facilities planning. Prerequisite: I E 425

I E 516 (SC&IS) APPLIED STOCHASTIC PROCESSES ( 3) Effective Date: SP2006 Study of stochastic processes and their applications to engineering and supply chain and information systems. Prerequisite: I E 322 or STAT 318

I E 519 (SC&IS) DYNAMIC PROGRAMMING ( 3) Effective Date: SP2006 Theory and application of dynamic programming; Markov decision processes with emphasis on applications in engineering systems, supply chain and information systems. Prerequisite: I E 516 or SC&IS 516 or equivalent

I E 520 MULTIPLE CRITERIA OPTIMIZATION ( 3) Study of concepts and methods in analysis of systems involving multiple objectives with applications to engineering, economic, and environmental systems. Prerequisite: I E 405 or B A 450

I E 521 NONLINEAR PROGRAMMING ( 3) Fundamental theory of optimization including classical optimization, convex analysis, optimality conditions and duality, algorithmic solution strategies, variational methods in optimization. Prerequisite: I E 505

I E 522 DISCRETE EVENT SYSTEMS SIMULATION ( 3) Fundamentals of discrete event simulation, including event scheduling, time advance mechanisms, random variate generation, and output analysis. Prerequisite: I E 425

I E 532 RELIABILITY ENGINEERING ( 3) Mathematical definition of concepts in reliability engineering; methods of system reliability calculation; reliability modeling, estimation, and acceptance testing procedures. Prerequisite: I E 323 or 3 credits in probability and statistics with a prerequisite of calculus

I E 554 PRODUCTION, PLANNING, AND CONTROL ( 3) Analysis of research literature for topics including scheduling, capacity planning, and lot sizing applied to manufacturing and production. Prerequisite: I E 455 , I E 507

I E 562 EXPERT SYSTEMS DESIGN IN INDUSTRIAL ENGINEERING ( 3) Methodological aspects of expert systems design and review of some existing systems with emphasis on manufacturing and industrial engineering. Prerequisite: I E 450 , background in one programming language would be useful

I E 566 QUALITY CONTROL ( 3) Advanced quality assurance and control topics, including multivariate methods, economic design for control and acceptance, dimensioning, tolerancing, and error analysis. Prerequisite: I E 423

MATH 414 (STAT) INTRODUCTION TO PROBABILITY THEORY ( 3) Probability spaces, discrete and continuous random variables, transformations, expectations, generating functions, conditional distributions, law of large numbers, central limit theorems. Students may take only one course from MATH(STAT) 414 and 418 for credit. Prerequisite: MATH 230 or MATH 231

MATH 415 (STAT) INTRODUCTION TO MATHEMATICAL STATISTICS ( 3) A theoretical treatment of statistical inference, including sufficiency, estimation, testing, regression, analysis of variance, and chi-square tests. Prerequisite: MATH 414

MATH 416 (STAT) STOCHASTIC MODELING ( 3) Review of distribution models, probability generating functions, transforms, convolutions, Markov chains, equilibrium distributions, Poisson process, birth and death processes, estimation. Prerequisite: MATH 318 OR MATH 414 ; MATH 230

MATH 418 (STAT) PROBABILITY ( 3) Fundamentals and axioms, combinatorial probability, conditional probability and independence, probability laws, random variables, expectation; Chebyshev's inequality. Students may take only one course from MATH(STAT) 414 and 418 for credit. Prerequisite: MATH 230 or MATH 231

MATH 451 (CSE) NUMERICAL COMPUTATIONS ( 3) Algorithms for interpolation, approximation, integration, nonlinear equations, linear systems, fast FOURIER transform, and differential equations emphasizing computational properties and implementation. Students may take only one course for credit from MATH 451 and 455. Prerequisite: CMPSC 201C , CMPSC 201F , or CSE 103 ; MATH 230 or MATH 231

MATH 455 (CSE) INTRODUCTION TO NUMERICAL ANALYSIS I ( 3) Floating point computation, numerical rootfinding, interpolation, numerical quadrature, direct methods for linear systems. Students may take only one course for credit from MATH 451 and MATH 455. Prerequisite: CMPSC 201C , CMPSC 201F , or CSE 103 ; MATH 220 ; MATH 230 or MATH 231

MATH 456 (CSE) INTRODUCTION TO NUMERICAL ANALYSIS II ( 3) Polynomial and piecewise polynomial approximation, matrix least squares problems, numerical solution of eigenvalue problems, numerical solution of ordinary differential equations. Prerequisite: MATH 455

MATH 484 LINEAR PROGRAMS AND RELATED PROBLEMS ( 3) Introduction to theory and applications of linear programming; the simplex algorithm and newer methods of solution; duality theory. Prerequisite: MATH 220 ; MATH 230 or MATH 231

MATH 485 GRAPH THEORY ( 3) Introduction to the theory and applications of graphs and directed graphs. Emphasis on the fundamental theorems and their proofs. Prerequisite: MATH 311W

MATH 486 MATHEMATICAL THEORY OF GAMES ( 3) Effective Date: SP2006 Basic theorems, concepts, and methods in the mathematical study of games of strategy; determination of optimal play when possible. Prerequisite: MATH 220

MATH 516 STOCHASTIC PROCESSES ( 3) Markov chains; generating functions; limit theorems; continuous time and renewal processes; martingales, submartingales, and supermartingales; diffusion processes; applications. Prerequisite: MATH 416

MATH 519 (STAT) TOPICS IN STOCHASTIC PROCESSES ( 3) Selected topics in stochastic processes, including Markov and Wiener processes; stochastic integrals, optimization, and control; optimal filtering. Prerequisite: STAT 516 , STAT 517

MATH 549 MATHEMATICAL PROGRAMMING ( 3) Quadratic and convex programming, integer and combinatorial programming, dynamic and stochastic programming. Prerequisite: MATH 484

MATH 550 (CSE) NUMERICAL LINEAR ALGEBRA ( 3) Solution of linear systems, sparse matrix techniques, linear least squares, singular value decomposition, numerical computation of eigenvalues and eigenvectors. Prerequisite: MATH 441 or MATH 456

MATH 555 (CSE) NUMERICAL OPTIMIZATION TECHNIQUES ( 3) unconstrained and constrained optimization methods, linear and quadratic programming, software issues, ellipsoid and Karmarkar's algorithm, global optimization, parallelism in optimization. Prerequisite: MATH 456

M E M 510 PRODUCTION AND OPERATIONS MANAGEMENT ( 3 - 9) Overall planning, design, and selection of equipment; programming and scheduling of mineral operations; statistical control of costs and production indices.

MKTG 511 QUANTITATIVE ANALYSIS FOR MARKETING DECISIONS ( 3) Application of quantitative and analytical tools for marketing decisions in forecasting, new product development, advertising, promotions, pricing, and personal selling. Prerequisite: MKTG 500

MKTG 555 (MS&IS) MARKETING MODELS ( 3) Topics in the model building approach to marketing decision making, focusing on current research issues.

MN PR 520 MATHEMATICAL MODELING FOR MINERAL PROCESS ENGINEERS ( 3) Techniques for setting up mathematical models of physical processes of interest in mineral process engineering; analytical and computational methods of solution. Prerequisite: MATH 250

O R 590 COLLOQUIUM ( 1 - 3) Continuing seminars which consist of a series of individual lectures by faculty, students, or outside speakers.

P N G 430 RESERVOIR MODELING ( 3) The numerical simulation of petroleum reservoir processes by the use of models; scaling criteria and network flow. Prerequisite: MATH 251 , P N G 410 ; CMPSC 201C or CMPSC 201F

P N G 511 NUMERICAL SOLUTION OF THE PARTIAL DIFFERENTIAL EQUATIONS OF FLOW IN POROUS MED IA ( 3) Differencing schemes for the partial differential equations of single-phase flow; application to flow of gas and mixing in porous media.

P N G 512 NUMERICAL RESERVOIR SIMULATION ( 3) Mathematical analysis of complex reservoir behavior and combination drives; numerical methods for the solution of behavior equations; recent developments.

P N G 514 OPTIMIZATION OF PETROLEUM RECOVERY PROCESSES ( 3) Optimum search methods, linear programming, nonlinear programming, dynamic programming, application to water-flooding, depletion drive, steam injection, gas cycling, miscible displacement. Prerequisite: P N G 410

STAT 460 INTERMEDIATE APPLIED STATISTICS ( 3) Review of hypothesis testing, goodness-of-fit tests, regression, correlation analysis, completely randomized designs, randomized complete block designs, latin squares. Prerequisite: STAT 200 , STAT 240 , STAT 250 , STAT 301 , or STAT 401

STAT 501 REGRESSION METHODS ( 3) Analysis of research data through simple and multiple regression and correlation; polynomial models; indicator variables; step-wise, piece-wise, and logistic regression. Prerequisite: 6 credits in statistics or STAT 451 ; matrix algebra

STAT 502 ANALYSIS OF VARIANCE AND DESIGN OF EXPERIMENTS ( 3) Analysis of variance and design concepts; factorial, nested, and unbalanced data; ANCOVA; blocked, Latin square, split-plot, repeated measures designs. Prerequisite: STAT 462 or STAT 501

STAT 503 DESIGN OF EXPERIMENTS ( 3) Design principles; optimality; confounding in split-plot, repeated measures, fractional factorial, response surface, and balanced/partially balanced incomplete block designs. Prerequisite: STAT 462 or STAT 501 ; STAT 502

STAT 510 APPLIED TIME SERIES ANALYSIS ( 3) Identification of models for empirical data collected over time. Use of models in forecasting. Prerequisite: STAT 462 or STAT 501 or STAT 511

STAT 513 THEORY OF STATISTICS I ( 3) Probability models, random variables, expectation, generating functions, distribution theory, limit theorems, parametric families, exponential families, sampling distributions. Prerequisite: MATH 230

STAT 514 THEORY OF STATISTICS II ( 3) Sufficiency, completeness, likelihood, estimation, testing, decision theory, Bayesian inference, sequential procedures, multivariate distributions and inference, nonparametric inference. Prerequisite: STAT 513

STAT 515 STOCHASTIC PROCESSES I ( 3) Conditional probability and expectation, Markov chains, the exponential distribution and Poisson processes. Prerequisite: MATH 414 , STAT 414 , or STAT 513

STAT 540 STATISTICAL COMPUTING ( 3) Computational foundations of statistics; algorithms for linear and nonlinear models, discrete algorithms in statistics, graphics, missing data, Monte Carlo techniques. Prerequisite: STAT 501 or STAT 511 ; STAT 415 ; matrix algebra

SC&IS 505 MANAGEMENT INFORMATION SYSTEMS RESEARCH ( 1 - 3) Effective Date: SP2006 Research problems and issues in supply chain and information systems.

SC&IS 510 INTRODUCTION TO SUPPLY CHAIN AND INFORMATION SYSTEMS ( 3) Effective Date: SP2006 Introduction to the strategic framework, issues, and methods for integrating supply and demand management within and across companies.

SC&IS 520 PRINCIPLES OF SC&IS I ( 3) Effective Date: SP2006 Initial course on principles of supply chain and information systems with special emphasis on potential research topics. Prerequisite: SC&IS 510

SC&IS 525 SUPPLY CHAIN OPTIMIZATION ( 3) Effective Date: SP2006 Introduction to theory and practice of optimization methods and models for analyzing and improving the performance of supply chain environments. Prerequisite: prior coursework in linear algebra and calculus

SC&IS 530 PRINCIPLES OF SC&IS II ( 3) Effective Date: SP2006 Sequel on principles of supply chain and information systems with special emphasis on potential research topics. Prerequisite: SC&IS 510

SC&IS 535 STATISTICAL RESEARCH METHODS FOR SUPPLY CHAIN AND INFORMATION SYSTEMS ( 3) Effective Date: SP2006 Current statistical research methods for modeling and analysis of supply chain and information systems. Prerequisite: 3 credits each in undergraduate accounting, economics, and statistics

SC&IS 545 SUPPLY CHAIN SYSTEMS SIMULATION ( 3) Effective Date: SP2006 Application of computer simulation to analysis and design of supply chain and information systems design; simulation experiments in SC&IS research. Prerequisite: 3 credits of computer programming

SC&IS 546 PROCUREMENT AND SUPPLY MANAGEMENT ( 3) Effective Date: SP2006 Analysis, planning, and management of domestic and international procurement and supply activities.

SC&IS 565 SUPPLY CHAIN STRATEGY ( 3) Effective Date: SP2006 Strategies, issues and best practices in technology adoption, change management, financial/capability assessments, critical aspects of relationship management in supply-chain networks. Prerequisite: SC&IS 510

Participating Programs

To pursue a dual-title degree in Operations Research at Penn State the student must apply for admission to the Graduate School and select one of the following graduate major programs: (Contact is made through the Graduate Advisor for each program)

Agricultural, Environmental & Regional Economics Agricultural & Biological Engineering Animal Science Architectural Engineering Business Administration Chemical Engineering Civil Engineering Computer Science & Engineering Economics Education Electrical Engineering Entomology Environmental Chemistry and Geochemistry Forest Resources Geosciences Geography Hotel, Restaurant, and Institutional Management Industrial Engineering Mathematics Mineral Economics Mining Engineering Petroleum & Natural Gas Engineering Poultry Science Statistics Workforce Education and Development