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Course Descriptions

IE 501 – Probability Theory and Applications                                                                 (3-0) 7.5                                                                  

Basic concepts in probability and statistics (counting, sample spaces, events, random variables … etc), probability distributions, mean value, variance and high-order moments; independence and conditional probability; common, marginal and conditional distributions, covariance and correlation; momemt generating functions; limit theorems.

IE 502 – Statistics Theory and Applications                                                                     (3-0) 7.5                                                                                           

Concepts of descriptive statistics; univariate analysis: sample distribution, central tendency, dispersion; bivariate and multivariate analyses: scatter plots, association, correlation, causality; concepts, theory and techniques of inferential statistics; hypothesis testing: design, choice of method, significance level; comparing and contrasting two samples; fitting a distribution to a data sample: choice of appropriate distribution, fitting method, parameter estimation, evaluation and interpretation of goodness of the fit; linear and non-linear regression, analysis of variance (ANOVA); multivariate analysis and factor models; associated computer modeling/analysis and visual data presentation methods.

IE 512 – Optimization Methods II                                                                                      (3-0) 7.5

Integer linear programming (IP): problem formulation, big-M method, integrality property, branch-and-bound method; introduction to dynamic programming (DP) and Markov decision processes (MDP); introduction to goal programming (GP) and multi-objective optimization.

IE 513 – Dynamic Programming                                                                                         (3-0) 7.5

Dynamic programming problem formulation; solution techniques for generic dynamic programming problems; shortest-path algorithm; deterministic equipment replacement problem; resource allocation problem; traveling salesman problem; dynamic programming applications in inventory management; generic stoshastic formulation; Markov decision processes.

IE 514 – Non-linear Programming                                                                                     (3-0) 7.5                                                                          

Classical optimization theory: optimization in one variable, convexity, unconstrained and constrained optimization in many variables, Karush-Kuhn-Tucker optimality conditions, Lagrange functions, existence and uniqueness theorems, global and local optima; nonlinear programming (NLP): direct search and gradient methods; indirect methods: conjugate gradient, Hooke and Jeeves etc.

IE 519 - Operations Research Modeling Applications                                                   (3-0) 7.5

Review of mathematical programming: theory, modeling concepts, techniques; the General Algebraic Modeling System (GAMS): syntax basics, options, solvers, advanced features; various modeling applications including but not limited to: variants of the transportation problem, shortest path problem, maximum flow problem, traveling salesperson problem, assignment problem; other applications depending on instructor’s specialization and interests.

IE 521 – System Simulation                                                                                                 (3-0) 7.5              

Introduction to simulation modeling; input data modeling; validation and verification of models; output data analysis; random number generation methods; comparison of systems using simulation; simulation optimization; variance reduction methods; system dynamics; computer programming techniques in simulation.                                                           

IE 527 – Queueing Systems                                                                                                 (3-0) 7.5                                                                           

Elements and classification of queueing systems; exponential and single server queueing systems; exponential and multi-server queueing systems; advanced exponential queueing models; open and closed Jackson networks; queues with general arrival and service distributions.

IE 530 – Inventory Planning                                                                                                (3-0) 7.5                                                                          

The context and importance of inventory management; basic economic order quantity model; quantity discounts; single item inventory models: time variant demand, stochastic demand, newsvendor model; stochastic lead times; continuous and periodic review: (s, Q), (s, S), (R, S), and (R, s, S) models; ABC inventory management; models with perishable goods; coordinated replenishment; multiechelon inventory systems.

IE 540 – Scheduling                                                                                                               (3-0) 7.5                                                                          

Machine scheduling: deterministic single machine; flow shop, and job shop scheduling; project scheduling: overview of CPM (critical path method) and PERT (project evaluation and review technique); time-cost trade-offs; workforce scheduling; crew scheduling; advanced single machine scheduling; deterministic parallel machine scheduling; flexible flow shop scheduling.

IE 542 – Supply Chain Management                                                                                  (3-0) 7.5                                                                                                                                                 

Stochastic inventory models; risk pooling; multi-echelon inventory models; value of information in supply chains; bullwhip effect; logistics network configuration; distribution strategies; centralized vs. decentralized control; supply chain contracts; strategic alliances.

IE 570 – Decision Analysis                                                                                                   (3-0) 7.5

Framing decision problems; decision trees and influence diagrams; decision making under uncertainty; sensitivity analysis; expected utility theory; alternative theories for modeling decisions, behavioral approaches; risk; value of information; analytic hierarchy process (AHP); introduction to multi-criteria decision analysis.  

IE 571 – Advanced Engineering Economics                                                                      (3-0) 7.5

Economic and financial aspects of engineering decision making; time value of money; basic interest formulas; annual, present and future value analysis; internal and external rates of return; depreciation and taxes; multiple investment/project alternatives; timing of equipment replacement; evaluation and comparison of loans, leases and financial investments; risk aversion and investments with uncertain returns; bonds, forwards and options; fundamentals of portfolio analysis; associated computer analysis and programming skills.

IE 572 – Multi-Criteria Decision Analysis                                                                         (3-0) 7.5

Framing and modeling multi-criteria decision problems; value and utility functions; multi-criteria decision trees; Pareto efficiency and Pareto efficient frontier; introduction to multi-criteria optimization; fundamental and alternative algorithms for approximating or finding the Pareto front.

IE 573 – Financial Engineering I                                                                                          (3-0) 7.5

Investments and markets; theory of interest; fixed-income securities; term structure of interest rates; mean-variance portfolio theory; capital asset pricing model; factor models and data; general principles  of investment.

 

IE 574 – Financial Engineering II                                                                                         (3-0) 7.5

Forwards, futures, and swaps; models of asset dynamics; basic options theory; additional options topics; interest rate derivatives; optimal portfolio growth; general investment evaluation and pricing. 

IE 575 – Engineering and Technology Management                                                      (3-0) 7.5

Engineering management concepts; processes of qualitative and quantitative management; management of technical and scientific organizations; systems theory; management and the systems concept; strategic planning and management systems; systems analysis; project management; cost management; organizational design; evaluation and control of systems; managing technical professionals; leadership; case studies and contemporary managerial issues.

IE 576 – Time Series Analysis                                                                                              (3-0) 7.5

Univariate time series analysis: autoregressive and moving average models; forecasting methods; smoothing; analysis of time series with trend and seasonality; modeling volatility using ARCH and GARCH; vector autoregressive models for the analysis of multivariate time series.

IE 577 – Game Theory Applications in Operations Research                                       (3-0) 7.5

Brief overview of the mathematical theory of games; non-zero sum games: strategies, Nash equilibrium, response functions; matrix games, strategic form games, Nash recursion, pure and mixed equilibria; sequential games: extensive-form representation, perfect and imperfect information, sequential equilibrium, sequential rationality, subgame perfect equilibrium; modeling games as mathematical programming problems, solution characterization, solution strategies and relevant optimization techniques; applications: auction design, oligopoly competition, manufacturer-retailer bargaining, capacity/congestion pricing, etc; static games of incomplete information: static Bayesian games and Bayesian Nash equilibrium, auction theory, mechanism design.

IE 581 – Special Topics in Industrial Engineering I                                                          (3-0) 7.5

Special topics of current interest which are not included within the other courses of the graduate program in industrial engineering. 

IE 582 – Special Topics in Industrial Engineering II                                                        (3-0) 7.5

Special topics of current interest which are not included within the other courses of the graduate program in industrial engineering.  

IE 511 – Optimization Methods I                                                                                       (3-0) 7.5

Mathematical modeling concepts; linear programming (LP): problem formulation, simplex and dual simplex methods, duality and sensitivity analysis; transportation model and its variants; network models.

IE 525 – Stochastic Models                                                                                                  (3-0) 7.5

Discrete and continuous Markov chains, birth-and-death processes, applications to queuing theory, a brief introduction to decision theory: decision trees, expected value of perfect information.

IE 590 – Seminar and Scientific Research Methods                                                       (2-0) 7.5

Seminars will be held by academics who conduct research in various areas of industrial engineering and the students who make progress towards completion of their thesis. In addition, an overview of scientific research methods will be given.

IE 597 – Project Course in Industrial Engineering                                                            15 ECTS

Students individually or in groups, choose, define, formulate, and resolve a real industrial engineering problem, preferably from a local firm or institution. Oral presentation and report required. An advisor will be assigned to supervise the students.

 

IE 598 – Master’s Thesis I                                                                                                        30 ECTS

Students individually prepare thesis under supervision of a faculty member. Thesis topic will be determined by a student and a faculty member who agrees to supervise the student.

 

IE 599 – Master’s Thesis II                                                                                                       30 ECTS

In continuation of the studies initiated as part of IE 598, students individually prepare thesis under supervision of a faculty member. Thesis topic will be determined by a student and a faculty member who agrees to supervise the student.