Master's Program

Master's Program Course Descriptions

IE 501 Linear Optimization Methods (3 0 3) (ECTS: 7.5)
Mathematical development of simplex algorithm. Formulation of various problems as linear programming problems. Duality theory and economic interpretations. The revised dual simplex and primal-dual simplex methods. Special forms of linear programming problems and their solution methods. Sensitivity and post-optimality analysis. Parametric programming.

IE 502 Stochastic Processes (3 0 3) (ECTS: 7.5)
Introduction to probability theory. Random variables. Expectations. Conditional probability. Discrete-time Markov chains. Exponential distribution and Poisson process. Continuous-time Markov chains. Renewal theory.

IE 505 Production Planning and Scheduling (3 0 3) (ECTS: 7.5)
Analysis of production activities. Aggregate production planning. Lot sizing. Material requirements planning. Cutting stock. Line balancing.

IE 507 Nonlinear Optimization Methods (3 0 3) (ECTS: 7.5)
Concept of convexity for functions and sets. Kuhn-Tucker conditions and Lagrangian duality. Quadratic programming. Steepest descent, Newton-type, quasi-Newton and gradient methods for unconstrained optimization. Penalty and barrier methods for constrained optimization.

IE 508 Graph Theory with Applications (3 0 3) (ECTS: 7.5)
Basics of graph theory. Directed and undirected graphs, and subgraphs. Shortest path and spanning tree algorithms. Solution techniques for maximum flow and minimal cost flow problems. Multi-commodity networks and graph representations. Network simplex algorithm. Applications in scheduling and sequencing.

IE 509 Queuing Theory (3 0 3) (ECTS: 7.5)
An introduction of queuing systems and their basic properties. Analysis of birth and death processes. Single- and multi-server queues. Batch server queues. Chapman-Kolmogorov equation and its implementations. Markov chains. Applications in manufacturing and service systems.

IE 510 Quality Management (3 0 3) (ECTS: 7.5)
History and philosophy of quality. Total quality management. Quality engineering techniques. Strategic management. Customer satisfaction, retention, and loyalty. Employee empowerment, leadership and change. Teamwork and effective communication. Standardization, certification and quality awards. ISO 9001 Quality Management System. Graphical tools for quality improvement. Continual improvement methods with just-in-time, six sigma and lean. Quality management in service sector. Implementing total quality management. Other quality management systems.

IE 511 Discrete Optimization Methods (3 0 3) (ECTS: 7.5)
Dynamic programming. Integer programming. Mixed-integer programming. Zero-one programming. Knapsack problems. Cutting planes and polyhedral approach. Branch and bound methods. Lagrangian relaxation. Heuristics. Nonlinear integer programming. Applications in various areas.

IE 512 Decision Analysis (3 0 3) (ECTS: 7.5)
Fundamentals of decision analysis. Utility measures and risk preference. Risk assessment. Use of decision trees with risk and time preference. Value of sampled and perfect information. Bayesian decision making under uncertainty.

IE 513 Inventory Theory (3 0 3) (ECTS: 7.5)
Study of inventory systems. Inventory costs. EOQ model. Deterministic and stochastic models with fixed or variable reorder intervals and lead times. Multi-echelon models. Heuristic solutions to some inventory models.

IE 514 Scheduling in Manufacturing Systems (3 0 3) (ECTS: 7.5)
Classification of scheduling problems and an overview of computational complexity theory. Deterministic scheduling and sequencing problems: single-stage, parallel machine, and multi-stage (open shop, flow shop, job shop, mixed shop) manufacturing environments. Dispatching. Exact solution techniques: linear (integer) programming, branch-and-bound methods, dynamic programming. Approximate solution techniques: Metaheuristics (simulated annealing, tabu search, genetic algorithms), constructive algorithms. Applications to the real-life problems.

IE 519 Humanitarian Logistics (3 0 3) (ECTS: 7.5)
This course provides the basic concepts of humanitarian logistics and an application of Operations Research/Management Science tools to the operational phases of humanitarian logistics. Covered topics are Introduction to humanitarian logistics; Operational phases of humanitarian logistics; Characteristics of humanitarian logistics; Needs assessment phase; Procurement; Facility and warehouse location; Transportation and distribution; Technology and information management; Coordination of different stakeholders; Recovery phase and sustainment phase; Performance management.

IE 527 Simulation Modelling and Analysis (3 0 3) (ECTS: 7.5)
Simulation methodology. Overview of simulation tools. Model formulation. Selecting input distributions. Parameter estimation and distribution fit. Generating and testing random varieties. Model validation. Statistical analysis of simulation output. Variance reduction techniques. Design and analysis of experiments. The use of simulation for estimation, comparison of policies. Applications of simulation modelling in manufacturing, material handling, logistics and service systems.

IE 551 Multi-Criteria Decision Making (3 0 3) (ECTS: 7.5)
Overview and definitions of Multiple Criteria Decision Making (MCDM) concept. Decision space, objective space, convex sets, functions and test for convexity. MCDM examples. Decision analysis and utility theory. Basic techniques used in decision making for complex systems. Value of information, the concept of utility theory. Formulation of the general multiple criteria programming, classification of multiple criteria programming methods, decision making with discrete and continuous alternatives. Goal Programming, algorithms for goal programming, method of global criterion and compromise programming, multi parametric decomposition, multi criteria simplex method. Interactive approaches for MCDM.

IE 552 Heuristic Methods for Optimization (3 0 3) (ECTS: 7.5)
This course covers applications and developments of heuristic search methods for solving complex optimization problems, detailing various local search strategies including genetic algorithms, simulated annealing, and tabu search.

IE 555 Logistics Engineering (3 0 3) (ECTS: 7.5)
Introduction to business logistics. Facility Location Decisions. Covering Problems. Center and Median Problems. Fixed Charge Facility Location Problems. Transportation Decisions. Vehicle routing problems. Inventory policy decisions. Storage and handling systems. Combined models. Contemporary issues (Carbon footprint, sustainability, information systems etc.).

IE 560 Supply Chain Management (3 0 3) (ECTS: 7.5)
This course covers main elements of supply chain management with emphasis on quantitative models for integrating procurement, operations, and logistics. Definition of supply chain; planning models to aid in designing supply chain networks; planning demand and supply including models for forecasting, aggregate planning, sales and operations planning and coordination; commonly used inventory models and their management; designing and planning of transportation networks; managing cross-functional drivers including sourcing decisions, pricing and revenue management, information technology and sustainability.

IE 574 Advanced Project Scheduling (3 0 3) (ECTS: 7.5)
Basic concepts and classification of project scheduling problems. Scheduling in the absence of resource constraints. Critical path method and PERT analysis. Project scheduling with start-time dependent costs. Preemptive and generalized resource-constrained project scheduling. Resource levelling and availability cost problem. Weighted earliness-tardiness costs. Nonrenewable resource constraints. Project scheduling to maximize the net present value of the project. Discounted cash flows. Multiple activity execution modes. Multi project scheduling. Project monitoring and control.

IE 590 Graduate Seminar (Non credit) (ECTS: 7.5)
This course is a required course for students who are enrolled in the thesis option. Each student gives a seminar related to an Industrial Engineering research project conducted under the supervision of his/her academic advisor.

IE 592 Graduate Project (Non credit) (ECTS: 15)
This course is a required course for students who are enrolled in the non-thesis option. Under the supervision of an academic advisor, each student conducts a project study with a topic in Industrial Engineering and submit a written report.

IE 599 Master's Thesis (Non credit) (ECTS: 60)
This course is a compulsory course for students who are enrolled in the non-thesis option. Under supervision of an academic advisor, the student is required to study on a project topic from industrial engineering area. Upon the completion of the project study, the student prepares a project report and given an oral presentation.