The Ph.D. Program in Industrial Engineering comprises a minimum number of 24 credits of course work and a dissertation carried out according to the regulations of the Institute. The program for students with an M.S. degree in Industrial Engineering from Bogaziçi University will be determined according to the needs of the student by his/her advisor, subject to the approval of the Institute. Other students must satisfy the course requirements of the Industrial Engineering Master of Science Program. Some or all of these requirements can be met through equivalent courses taken in other graduate programs. The regular Ph.D. program will be determined according to the needs of the student by his/her advisor, subject to the approval of the Institute.
COURSE DESCRIPTIONS
IE 501 Optimization Techniques I (Eniyileme Teknikleri I) (3+0+0) 3
Linear programming modeling; linear algebra, convex analysis, polyhedral sets; simplex method; modeling with GAMS; algorithmic complexity; the computational efficiency of the simplex method; efficient simplex implementations; duality and the sensivity analysis; decomposition principle; computational complexity; the complexity of linear programming; interior point methods; introduction to convex programming. Prerequisite: IE 310 or equivalent.
IE 502 Optimization Techniques II (Eniyileme Teknikleri II) (3+0+0) 3
Integer programming; cutting plane, branch and bound methods; Lagrangean relaxation and subgradient optimization; optimality conditions for nonlinear programming; basic algorithms for unconstrained and constrained nonlinear programming; dynamic programming. Prerequisite: IE 310 or equivalent.
IE 503 Methods of Industrial Engineering (3+0+0) 3
(Endustri Muhendisligi Metodlari)
Investment decisions; facility location, capacity, layout; aggregate planning and master scheduling; inventory control; material requirements planning; production scheduling and control; project planning and control; quality control; maintenance planning.
IE 504 Probability Theory and Statistics for Industrial Engineers (3+0+0) 3 ECTS 7
(Endustri Muhendisleri icin Olasilik Kurami ve Istatistik)
Basic probability theory: Sample space, events, probability, and conditional probability. Discrete and continuous random variables; marginal, joint and conditional distributions; expectations and conditional expectations. Inferential statistics: Sampling theory; parameter estimation, point and interval estimation and hypothesis testing. Applications in industrial engineering and operations research using statistical software packages.
IE 505 Stochastic Processes and Applications (3+0+0) 3 ECTS 7
(Rassal Surecler ve Uygulamalari )
Random variables and stochastic processes: Generating functions, Bernouilli and Branching processes, Poisson processes and applications in traffic models. Renewal and regenerative processes and applications in inventory control and reliability models. Markov chains and Markov processes with applications in queueing models. Introduction to Brownian motion with financial applications. Prerequisite: IE 504 or IE 255 or consent of instructor.
IE 506 Design and Analysis of Experiments (3+0+0)3 ECTS 7
(Deney Tasarimi ve Cozumlemesi)
Design of experiments methodology; simple comparative experiments; single factor experiments; randomized blocks; Latin square designs; factorial designs; fractional factorial designs; regression models; response surface methodology; random effects models; nested and split plot designs; robust designs; mixture designs; optimal designs. Prerequisite: IE 504 or equivalent.
IE 508 Statistical Inference (Istatistiksel Cikarim) (3+0+1) 3 ECTS 7
Estimation Theory, sufficiency, maximum likelihood estimation, interval estimates, and hypothesis testing, Neyman-Pearson approach, likelihood ratio test, linear statistical models (regression and ANOVA), generalized linear models, and logistic regression. Applications in industrial engineering and operations research. Prerequisite: IE 504 or IE 256 or consent of instructor.
IE 510 Simulation Modeling and Analysis (3+0+0) 3
(Benzetim Modelleri ve Analizi)
Simulation methodology, model formulation, systems dynamics, overview of simulation languages, generating random varieties, output data analysis, model validation, variance reduction techniques, experimental design and optimization.
IE 514 Nonlinear Programming (Dogrusal Olmayan Programlama) (3+0+0) 3
Convex analysis; necessary and sufficient conditions for optimality, methods of unconstrained optimization, necessary and sufficient conditions for constrained optimization, methods for handling equality and inequality constraints, nonlinear programming methods such as primal methods and penalty function methods. Prerequisite: IE 310 or equivalent.
IE 515 Graphs and Network Flows (Çizgeler ve Serimlerde Akis) (3+0+0) 3
Introduction to graph theory; graph search; data structures for graph and network flow algorithms; shortest path problems; minimum spanning tree problem; matching in bipartite graphs; maximum flow - minimum cut and minimum cost circulation problems. Prerequisite: IE 310 or equivalent.
IE 516 Combinatorial Optimization (Birlesisel Eniyileme) (3+0+0) 3
Introduction to combinatorial optimization; shortest path problems; minimum spanning tree problem; maximum cardinality and weight matching problems in bipartite graphs; Hungarian algorithm; maximum cardinality and weight matching problems in general graphs; Edmond's algorithm; integral polyhedra; matroids; greedy algorithm. Prerequisite: IE 501 or equivalent.
IE 517 Heuristic Methods in Optimization (3+0+0) 3
(Eniyilemede Sezgisel Yontemler)
Introduction to heuristic methods; classical construction heuristics; classical improvement heuristics; Lagrangean relaxation, simulated annealing, tabu search. Neural networks, genetic algorithms, ant colony optimization. Prerequisite: IE 310 or consent of instructor.
IE 520 Quality Management (Kalite Yonetimi) (3+0+0) 3
Total quality management, quality assurance programs, quality circles, modeling process quality, statistical process control, acceptance sampling plans, quality information systems, organization for quality, quality cost models, quality design, recent issues in quality management.
IE 523 Design of Production Systems (3+0+0) 3 ECTS 7
(Uretim Sistemlerinin Tasarimi)
Continuous and discrete space facility location models, and location/allocation models. Facility layout models and solution methods. Group technology and cellular manufacturing, cell formation using clustering, mathematical programming and other methods. Design of flexible manufacturing, warehousing, distribution and logistic systems. Prerequisite: IE 312 or consent of instructor.
IE 524 Planning of Production Systems (Uretim Sistemlerinin Planlanmasi) (3+0+0) 3 ECTS 7
Overview of production systems and planning paradigms. Hierarchical planning, aggregation/disaggregation. Continuous and discrete lot-sizing models and solution methods. Distributed planning and coordination in supply chains. Prerequisite: IE 413 or consent of instructor.
IE 530 Mathematical Modeling in Industrial Engineering (2+0+2) 3
(Endustri Muhendisliginde Matematiksel Modelleme)
In this course practical aspects, applications and implementation problems of mathematical programming models will be discussed and analyzed. In particular, linear programming, integer programming, and multiobjective programming models will be considered. For these models, application areas, underlying assumptions, special technical considerations, typical implementation problems will be investigated. Many case studies and discussion papers on the topic will be analyzed and discussed. Prerequisite: IE 202 or equivalent.
IE 533 Systems Theory (Sistem Kurami) (3+0+0) 3
Conceptual foundations of systems theory. Analysis of linear continuous systems; stability, controllability, and observability; applications to physical, ecological, and socio-economic systems; feedback control systems; introduction to optimal control.
IE 542 Manufacturing Information Systems (2+0+2) 3
(Imalat Bilisim Sistemleri)
Information management for manufacturing enterprise integration with emphasis on concepts such as CIM and Concurrent Engineering, production management approaches such as MRP II, JIT and OPT, engineering functions such as CAD and CAPP, and Shop Floor Control. A development framework for an information system for Shop Floor Control: structured analysis for modelling information requirements, a reference model for system design; a review of information requirements, a reference model for system design; a review of information technology including state-of-the-art architectures and tools such as distributed systems, open systems, factory networks, communication standards, and database management systems. Prerequisite: IE 413 or equivalent.
IE 544 Decision Analysis (Karar Analizi) (3+0+0) 3
Bayesian decision theory; measurement theory; subjective probability. Dependency models; Bayesian networks; exact and approximate inference; computational complexity of inference. Influence diagrams; value of information; decision networks and connections to Markov decision processes. Case studies; risk sharing and decisions; implementation of decision models.
IE 546 Competitive Models in Supply Chain Management (3+0+0) 3 ECTS 7
(Arz Zinciri Yonetiminde Rekabetci Modeller )
Centralized and decentralized analysis of production and distribution systems. Existence and uniqueness of equilibrium in principal agent and simultaneous move games, information asymmetry, Bayesian games, cooperative games, dynamic games. Contract design, enforceability of contracts. Prerequisite: Consent of instructor.
IE 548 Stochastic Models for Manufacturing Systems (3+0+0) 3 ECTS 7
(Imalat Sistemleri icin Rassal Modeller )
Essentials of queueing theory, Jackson networks, queueing networks with finite buffers. Machine failures, analysis and modelling of transfer lines, assembly/disassembly lines, quality failures. Control of production systems: Kanban, base stock, continuous work-in-process (CONWIP). Prerequisite: IE 304 or IE 505 or consent of instructor.
IE 550 Dynamics of Socio-Economic Systems (2+1+1) 3
(Sosyo-Ekonomik Sistemlerin Dinamigi)
Use of systems thinking and system dynamics modeling methodology in the analysis of complex, dynamic socio-economic and managerial problems. Lab experiments with simulation models of real case studies ranging from ecological to business issues, from social to agricultural problems. Basic methods and tools of dynamic feedback modeling: stock-flow and causal loop diagrams, linear and non-linear equation formulation and generic structures. Use of a modern modeling/simulation software such as STELLA, VENSIM, POWERSIM. Student term projects involving applied dynamic modeling.
IE 578 Industial Engineering Seminar (0+1+0) 0 P/F
(Endustri Muhendisligi Semineri)
Seminar on recent and contemporary topics in industrial engineering, operations research, and related fields; presentations and discussions designed to fit the academic interests of the faculty as well as current issues in theory and practice.
IE 579 Graduate Seminar (Lisansustu Seminer) (0+1+0) 0 P/F
The widening of students' perspectives and awareness of topics of interest to industrial engineers through seminars offered by faculty, guest speakers and graduate students.
IE 580-599 Selected Topics in Industrial Engineering (3+0+0) 3
(Endustri Muhendisliginde Seçme Konular)
Current topics of interest in Industrial Engineering selected to suit both the class and the instructor.
IE 602 Dynamic Systems Modeling and Analysis (3+0+0) 3
(Dinamik Sistem Modellemesi ve Analizi)
The philosophy and fundamental concepts of systems theory, various mathematical and quasi-mathematical techniques for dynamic feedback modeling and analysis. Notions of equilibrium, stability and major types of non-linear dynamics; shift of loop dominance, path-dependence, limit cycles, multiple periods, bifurcations. Examples from socio-economic, managerial and other living systems. Suitable simulation/modeling software, spesifically for large-scale non-linear models. Student term project. Prerequisite: IE 550 or equvalent.
IE 605 Advanced Stochastic Processes (Ileri Rassal Sureçleri) (3+0+0) 3
Limiting behavior and potentials of Markov chains; Markov processes and infinitesimal generators; renewal theory and regenerative processes; Markov renewal processes; Brownian motion and its sample path analysis. Prerequisite: IE 505 or consent of instructor.
IE 608 Mathematical Statistics (Matematiksel Istatistik) (3+0+0) 3
Order statistics and related distributions; sufficiency and related theorems; point estimation, criteria for selecting estimators, methods of estimation; Neyman Pearson theory; likelihood ratio tests; Bayes and minimax procedures; sequential procedures; confidence estimation; general linear hypothesis; analysis of variance; non-parametric statistical inference. Prerequisite: IE 506 or consent of instructor.
IE 611 Integer Programming (Tamsayi Programlama) (3+0+0) 3
Modeling with integer variables; polyhedral combinatorics; theory of valid inequalities; disjunctive programming; duality and relaxation; linear programming relaxation; enumeration; branch-and-bound using linear programming relaxations; cutting plane algorithms; Lagrangean relaxation and duality; sub-gradient method; column generation technique; reformulation and linearization technique; lift-and-project method; problems with special structure. Prerequisite: IE 501 or consent of instructor.
IE 612 Dynamic Programming (Dinamik Programlama) (3+0+0) 3
Multi-stage problem solving; several state variables; recursive equations; principle of optimality; computational aspects; decomposition in dynamic programming and uncertainty; non-serial systems; dynamic programming and decision processes. Prerequisite: IE 501 or consent of instructor.
IE 613 Large Scale Programming (Buyuk Boyutlu Programlama) (3+0+0) 3
Decomposition, partitioning and compact inverse methods to deal with large and sparse optimization. Special structures such as Leontief substitution systems, production-inventory models. Simplex method with upper bounds and generalized upper bounding. Constraint relaxation methods. Branch and bound and Bender's partitioning methods to solve mixed integer linear programs. Prerequisite: IE 501 or consent of instructor.
IE 620 Investment Planning (Yatirim Planlamasi) (3+0+0) 3
Analysis of industrial projects, review of project appraisal techniques; technological feasibility; economic and financial feasibility; capital budgeting models; portfolio models; uncertainty and risk analysis; project management techniques; case studies.
IE 621 Inventory Control Theory (Envanter Kontrol Kurami) (3+0+0) 3
Description and characteristics of inventory models; economic order quantity and economic lot size models; multiple product and multiple location models under deterministic demand; stochastic single-item models with capacity constraints and lead-times; structure of dynamic inventory policies; multi-item stochastic demand inventory models; supply chain models and current issues in inventory planning. Prerequisite: IE 505 or consent of instructor.
IE 622 Reliability Theory and Applications (3+0+0) 3
(Guvenirlik Kurami ve Uygulamalari)
Analysis of deterministic, probabilistic and stochastic reliability models; coherent structures, min-path and min-cut representations, computing system reliability, reliability importance of components, systems with associated component, bounds on system reliability, stock and wear models, reliability operations and classes of life distributions, reliability improvement and allocation, availability theory for multi-component systems, optimal management of systems by replacement and preventive maintenance. Prerequisite: IE 505 or consent of instructor.
IE 624 Scheduling and Sequencing (Çizelgeleme ve Siralama) (3+0+0) 3
Theory and applications of analytical models used in the scheduling of operations. Topics include single and multi-machine scheduling, flow shop models, job shop models, hybrid models, assembly line balancing models. Evaluation of different scheduling rules in stochastic and dynamic production systems by means of analytical tools and simulation models.
IE 625 Queueing Theory (Kuyruk Kurami) (3+0+0) 3
Characterization of queuing systems; birth and death processes; single server queues; transient and equilibrium behavior; busy period; multiserver queues; batch service queues; non-Markovian queues; embedded Markov chains; bounds, inequalities and approximations; optimal control of queues; queuing networks. Prerequisite: IE 505 or consent instructor.
IE 628 Advanced Production Systems (Ileri Uretim Sistemleri) (3+0+0) 3
Impact of computer aided design and manufacturing on production planning; data base for manufacturing; classification and coding; manufacturing information systems; computer aided process planning; operations research models in assembly lines, automated flow lines, group technology, and flexible manufacturing systems.
IE 640 Advanced Information Systems (Ileri Bilisim Sistemleri) (3+0+0) 3
Implementation of information design concepts; management information systems; verification; auditing; checking and controlling information lost in the system; applications; case studies.
IE 642 Markovian Decision Processes (Markov Karar Sureçleri) (3+0+0) 3
Markov processes with rewards; value-iteration method for the solution of sequential decision processes; policy iteration method for the solution of sequential decision processes; Markovian decision processes with and without discounting; dynamic programming viewpoint of Markovian decision processes. Prerequisite: IE 505 or consent of instructor.
IE 680-689, 691-698 Special Topics in Industrial Engineering (3+0+0) 3
(Endustri Muhendisliginde Ozel Konular)
Advanced topics of interest in Industrial Engineering selected to suit both the class and the faculty.
IE 699 Guided Research (Yonlendirilmis Arastirmalar) (2+0+4) 4
Research in the field of Industrial Engineering, by arrangement with members of the faculty; guidance of doctoral students towards the preparation and presentation of a research proposal.