Course Descriptions of Undergraduate Departmental Electives
Course Descriptions of Undergraduate Departmental Electives
IE 402 Supply Chain Management (3 0 3) (ECTS: 5)
This course gives an understanding of the basic concepts, techniques and algorithms for planning and coordinating the supply chain systems. Moreover, it serves an opportunity to practice the tools taught in operations research and production planning courses. Topics to be covered: Introduction to the concepts and terminology of logistics and supply chain management, examination of components of logistics and supply chain systems, analysis of interactions and tradeoffs among these components, logistics network configuration, risk pooling and multi-echelon inventory systems, value of information in supply chains, coordination of the supply chain using contracts and other mechanisms, distribution strategies for the supply chain and product design for supply chain efficiency.
IE 404 Multiple Criteria Decision Making (3 0 3) (ECTS: 5)
This course is designed to cover quantitative decision analysis. The course is mainly divided into three parts, general introduction to decision analysis, multicriteria decision analysis, and multi-objective optimization. In the first part, how people make decisions and decision making traps are covered. The merits of a structured rational decision making process are emphasized. In the second part, the structuring of decision elements (values, objectives, alternatives, measures, tradeoffs, and uncertainty), multi-attribute utility theory (MAUT) and analytic hierarchy process (AHP) for decision under certainty, and decision trees for decisions under uncertainty are introduced. Value-added risk management is also discussed. Finally, in the third part, optimization and goal programming are discussed.
IE 406 Project Scheduling and Control (3 0 3) (ECTS: 5)
Project planning and control tools used in managing and delivering projects will be explained in depth. The topics covered in this course are project scheduling basics and models, resource constrained project scheduling: models and solution algorithms, project monitoring and control tools, and project risk analysis tools.
IE 411 Enterprise Resource Planning (3 0 3) (ECTS: 5)
Introduction to the business concept and content of the new economy. Fundamentals of Enterprise Resource Planning (ERP) systems concepts, and the importance of integrated information systems in an organization. ERP Systems are introduced to illustrate the concepts, fundamentals, framework, general information technology context, the technological infrastructure, and integration of business enterprise-wide application such as Supply Chain Management (SCM) and E-Commerce within the Business to Business (B2B) and Business to Consumer (B2C) context and discussions regarding the implementation of these systems.
IE 412 Applied Time Series Analysis (3 0 3) (ECTS: 5)
Introduction; time series; components of time series; autocorrelation; strong and weak stationarity; AR models, MA models; ARMA models; model identification and estimation; non-stationarity and unit root tests; ARIMA models; SARMA models; SARIMA models; model identification, estimation and forecasting of seasonal models; tests for seasonal unit roots.
IE 424 Discrete Location Models and Applications (3 0 3) (ECTS: 5)
Introduction and classification of location problems; overview of all the basic discrete facility location problems and the elements of location models; Single-Echelon Single-Commodity Location Models; Two-Echelon Multi-Commodity Location Models; Public Sector Location Models (Center, Median and Covering Problems); Hub Location Problems; basic Location-Routing Problems; modeling and solution methodologies for all location problem types covered.
IE 428 Quality Management Systems (3 0 3) (ECTS: 5)
This course teaches how to apply the concepts and tools of total quality to develop, implement, and maintain an effective quality assurance system in a manufacturing or service organization. Emphasis will be on both documentation and team-based strategies for continuous improvement, using the ISO 9000:2000 Standard as a basis for quality system requirements.
IE 435 Decision Analysis (3 0 3) (ECTS: 5)
Introduction; elements of decision problems; structuring decisions; probability and decision; decision making in a complex world; uncertainty and making choices; payoffs and losses; developing a decision model; non-probabilistic and probabilistic criteria for decision making under uncertainty; utility and the assessment of utility functions; decision tree analysis; gaining insight through evaluation; the value of information; terminal and posterior decisions; the value of perfect and sample information; pre-posterior analysis; using simulation to solve decision problems; getting agreement; implementing the decision analysis process.
IE 454 An Introduction to Combinatorial Analysis (3 0 3) (ECTS: 5)
The aim of this course is to develop better skills in understanding and formulating combinatorial models. Real life cases are studied. Software packages are used for solution and analysis of models.
IE 455 Defense Systems Analysis and Design (3 0 3) (ECTS: 5)
This course addresses at an introductory level the generally accepted principles and models of Operations Research applied in a defense analysis context. Applications of operations research tools and techniques to defense related problems including important design characteristics of defense related sensors, systems and weapons. Reliability of systems, effect of information and technology considering the modern weapons, munitions and the sensors are also investigated.
IE 456 Mathematical Modeling and Applications (3 0 3) (ECTS: 5)
This course aims to develop skills in understanding and formulating deterministic mathematical models of complex systems. Transportation, distribution, location, production, and economic planning problems are investigated. Real life cases are studied. Software packages are used for solution and analysis of models.
IE 458 Mathematical Models in Defense Systems (3 0 3) (ECTS: 5)
Review of Military Operations Research, mathematical models in Defense Analysis; deterministic combat simulation (homogeneous, heterogeneous) models; stochastic (Lanchester, discrete-time) combat simulation (homogeneous, heterogeneous) models; weapon effectiveness index/attrition models; weapon system and munition planning models; hybrid land combat models; naval warfare simulation and modeling; air defense models.
IE 463 Value Creation and Innovation in Industrial Networks (3 0 3) (ECTS: 5)
Value concept; innovation concept; inter-enterprise relationships and cooperation; value creation and innovation in relationships; value chain; organization and structure of networks, supply-demand chains, production networks, strategic alliances, innovation systems and innovation networks, clusters of firms.
IE 465 Industrial Engineering Methods and Applications in Business Life (3 0 3) (ECTS: 5)
Several industrial engineering topics with their applications in real life systems, modeling of real life problems and the solution techniques of these models will be introduced. Topics covered; supply chain management, sales and after sales processes, financial accounting, ERP systems, network planning, data analysis. We start with an example (which can be a real business problem or a simplified version) with clearly defined questions that are often of managerial relevance. Then we solve the problem during the class. Finally we discuss managerial insights based on the analysis.
IE 469 Engineering Ethics (3 0 3) (ECTS: 5)
The aim of this course is to teach how to formulate and resolve typical ethical issues by analyzing simple examples as well as case studies. Different approaches and perspectives to ethical problem solving are outlined and compared. Codes of Ethics for various engineering fields are studied. Apart from basic concepts of engineering ethics the following are also included in the subject matter: conflicts of interest, exchange of favors, risk, safety, liability, obligations of engineers to their employers and the society, intellectual property rights, environmental impact, and conflicting cultural values.
IE 471 Inventory Planning and Control (3 0 3) (ECTS: 5)
The aim of this course is to develop better skills in understanding, formulating and building inventory planning and control models. Inventory policies for continuous-review and periodic review are covered for deterministic and stochastic cases. Analysis of mathematical models is made. Students are expected to conduct a literature survey for the purpose of finding a solution to a typical inventory problem as the requirement of a project work.
IE 473 Material Handling Systems (3 0 3) (ECTS: 5)
Introduction to planning and design of material handling systems, material handling terminology, principles, design procedure, analysis of material handling requirements, relationship with layout planning, unit load, material handling equipment selection, analysis of material transport systems (AGV, conveyor, monorail, cranes and hoists …), engineering analysis of storage systems (conventional vs. automated storage), warehousing, storage location strategies, storage system performance, equipment and space utilization.
IE 474 Scheduling and Sequencing (3 0 3) (ECTS: 5)
This course introduces the principles, techniques and algorithms for solving machine (resource) scheduling problems of the manufacturing and service systems. The topics covered in this course are overview of terminology, characteristics and classification of scheduling and sequencing problems, an overview of computational complexity theory, single machine, parallel machines, flow shop, job shop, and open shop scheduling problems with various scheduling criteria, dispatching rules, branch-and bound, dynamic programming, local search, and metaheuristic approaches.
IE 481 Optimization Techniques (3 0 3) (ECTS: 5)
Review of linear programming and simplex method; special forms of simplex algorithm; basics of nonlinear optimization; maxima, minima, and saddle points; algorithms for unconstrained nonlinear programming problems; methods for constrained nonlinear programming problems; Lagrange multipliers and Lagrange function; Kuhn-Tucker conditions; various nonlinear programming algorithms.