| IE 501 Linear Programming and Extensions |
3 Credits |
|
Theory of linear programming; convexity; simplex and
algorithmic aspects; duality and sensitivity; computational
issues; decomposition and column generation; introduction
to integer and nonlinear programming.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Fall 2023-2024 |
Linear Programming and Extensions |
3 |
| Fall 2022-2023 |
Linear Programming and Extensions |
3 |
| Fall 2021-2022 |
Linear Programming and Extensions |
3 |
| Fall 2020-2021 |
Linear Programming and Extensions |
3 |
| Fall 2019-2020 |
Linear Programming and Extensions |
3 |
| Fall 2018-2019 |
Linear Programming and Extensions |
3 |
| Fall 2017-2018 |
Linear Programming and Extensions |
3 |
| Fall 2016-2017 |
Linear Programming and Extensions |
3 |
| Fall 2015-2016 |
Linear Programming and Extensions |
3 |
| Fall 2014-2015 |
Linear Programming and Extensions |
3 |
| Fall 2013-2014 |
Linear Programming and Extensions |
3 |
| Fall 2012-2013 |
Linear Programming and Extensions |
3 |
| Fall 2011-2012 |
Linear Programming and Extensions |
3 |
| Fall 2010-2011 |
Linear Programming and Extensions |
3 |
| Fall 2009-2010 |
Linear Programming and Extensions |
3 |
| Fall 2008-2009 |
Linear Programming and Extensions |
3 |
| Fall 2007-2008 |
Linear Programming and Extensions |
3 |
| Fall 2006-2007 |
Linear Programming and Extensions |
3 |
| Fall 2005-2006 |
Linear Programming and Extensions |
3 |
| Fall 2004-2005 |
Linear Programming and Extensions |
3 |
| Fall 2003-2004 |
Linear Programming and Extensions |
3 |
| Fall 2002-2003 |
Linear Programming and Extensions |
3 |
| Fall 2001-2002 |
Linear Programming and Extensions |
3 |
| Fall 2000-2001 |
Linear Programming and Extensions |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 503 Stochastic Processes |
3 Credits |
|
Introduction to probability theory; random variables;
conditional probability and conditional expectation;
Poisson and renewal processes; discrete and continuous
Markov chains; applications in queuing, reliability,
inventory, production, and telecommunication problems.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Fall 2023-2024 |
Stochastic Processes |
3 |
| Fall 2022-2023 |
Stochastic Processes |
3 |
| Fall 2021-2022 |
Stochastic Processes |
3 |
| Fall 2020-2021 |
Stochastic Processes |
3 |
| Spring 2019-2020 |
Stochastic Processes |
3 |
| Spring 2018-2019 |
Stochastic Processes |
3 |
| Spring 2017-2018 |
Stochastic Processes |
3 |
| Spring 2016-2017 |
Stochastic Processes |
3 |
| Fall 2015-2016 |
Stochastic Processes |
3 |
| Fall 2014-2015 |
Stochastic Processes |
3 |
| Spring 2013-2014 |
Stochastic Processes |
3 |
| Spring 2012-2013 |
Stochastic Processes |
3 |
| Spring 2011-2012 |
Stochastic Processes |
3 |
| Spring 2010-2011 |
Stochastic Processes |
3 |
| Spring 2009-2010 |
Stochastic Processes |
3 |
| Spring 2008-2009 |
Stochastic Processes |
3 |
| Spring 2007-2008 |
Stochastic Processes |
3 |
| Fall 2006-2007 |
Stochastic Processes |
3 |
| Spring 2005-2006 |
Stochastic Processes |
3 |
| Spring 2004-2005 |
Stochastic Processes |
3 |
| Spring 2003-2004 |
Stochastic Processes |
3 |
| Spring 2002-2003 |
Stochastic Processes |
3 |
| Spring 2001-2002 |
Stochastic Processes |
3 |
| Spring 2000-2001 |
Stochastic Processes |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 509 Nonlinear Programming |
3 Credits |
|
Review on linear algebra and analysis, convex sets and
functions, quadratic programming, descent algorithm, line
search, conjugate directions, Newton's method, optimization
of nondifferentiable functions, necessary and sufficient
conditions for constrained optimization problems, duality
theory, penalty and barrier methods, Kuhn-Tucker methods,
introduction to semi-infinite and semidefinite optimization,
applications.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Fall 2022-2023 |
Nonlinear Programming |
3 |
| Spring 2020-2021 |
Nonlinear Programming |
3 |
| Fall 2017-2018 |
Nonlinear Programming |
3 |
| Spring 2014-2015 |
Nonlinear Programming |
3 |
| Spring 2012-2013 |
Nonlinear Programming |
3 |
| Fall 2011-2012 |
Nonlinear Programming |
3 |
| Fall 2009-2010 |
Nonlinear Programming |
3 |
| Fall 2007-2008 |
Nonlinear Programming |
3 |
| Fall 2005-2006 |
Nonlinear Programming |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 512 Graph Theory and Network Flows |
3 Credits |
|
Theory and applications of graphs and networks;
properties of graphs; Hamiltonian and Eulerian walk
problems; Travelling salesman problem and
variants; design and analysis of shortest path,
maximum flow and minimum cost network flow algorithms;
matching and assignment; network simplex
algorithm.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Fall 2023-2024 |
Graph Theory and Network Flows |
3 |
| Spring 2021-2022 |
Graph Theory and Network Flows |
3 |
| Spring 2019-2020 |
Graph Theory and Network Flows |
3 |
| Spring 2018-2019 |
Graph Theory and Network Flows |
3 |
| Spring 2017-2018 |
Graph Theory and Network Flows |
3 |
| Fall 2016-2017 |
Graph Theory and Network Flows |
3 |
| Spring 2015-2016 |
Graph Theory and Network Flows |
3 |
| Spring 2014-2015 |
Graph Theory and Network Flows |
3 |
| Spring 2013-2014 |
Graph Theory and Network Flows |
3 |
| Spring 2012-2013 |
Graph Theory and Network Flows |
3 |
| Fall 2011-2012 |
Graph Theory and Network Flows |
3 |
| Fall 2010-2011 |
Graph Theory and Network Flows |
3 |
| Spring 2009-2010 |
Graph Theory and Network Flows |
3 |
| Fall 2008-2009 |
Graph Theory and Network Flows |
3 |
| Spring 2007-2008 |
Graph Theory and Network Flows |
3 |
| Fall 2006-2007 |
Graph Theory and Network Flows |
3 |
| Fall 2005-2006 |
Graph Theory and Network Flows |
3 |
| Fall 2003-2004 |
Graph Theory and Network Flows |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 514 Manufacturing Strategies |
3 Credits |
|
Manufacturing and digitalization strategies methods and
means for the formulation of manufacturing and
digitalization strategies for securing long-term
competitiveness of the company; the alignment of
manufacturing and digitalization strategies with the
business and technology strategies of the company;
enabling technologies for digitalization; use of balanced
scorecard in strategy building; case studies.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2017-2018 |
Manufacturing Strategies |
3 |
| Fall 2015-2016 |
Manufacturing Strategies |
3 |
| Fall 2014-2015 |
Manufacturing Strategies |
3 |
| Spring 2007-2008 |
Manufacturing Strategies |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 515 Dynamic Programming |
3 Credits |
|
Dynamic programming (DP) is a general mathematical
technique used for making a sequence of
interrelated decisions and may be regarded as
an implicit scheme for enumerating
the various combinations of decisions in order to
identify an optimal policy. It is a widely
applied methodology in both deterministic and
stochastic optimization. Topics include but may
not be limited to the DP modeling and
the DP algorithm, deterministic systems and the shortest
path problem, problems with perfect state
information, problems with imperfect state
information, infinite horizon problems, infinite
horizon discounted problems, and stochastic
shortest path problems.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Fall 2021-2022 |
Dynamic Programming |
3 |
| Fall 2020-2021 |
Dynamic Programming |
3 |
| Fall 2019-2020 |
Dynamic Programming |
3 |
| Fall 2018-2019 |
Dynamic Programming |
3 |
| Fall 2017-2018 |
Dynamic Programming |
3 |
| Fall 2015-2016 |
Dynamic Programming |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 518 Queuing Theory and Applications |
3 Credits |
|
Application of the theory of stochastic processes to
queuing phenomena; steady-state analysis of birth-death
processes; Chapman-Kolmogorov
equations; Little's theorem and Markov property; arrival
and departure processes; Markovian queues; semi-Markov
processes; M/G/1, G/M/m, and G/G/1
queuing systems; literature readings and
presentations; Jackson networks; balance equations;
and stationary behavior.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Fall 2012-2013 |
Queuing Theory and Applications |
3 |
| Fall 2011-2012 |
Queuing Theory and Applications |
3 |
| Fall 2010-2011 |
Queuing Theory and Applications |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 522 Decision Analysis |
3 Credits |
|
Axiomatic foundations for probability and utility;
assessment of subjective and theoretical
probability distributions; formulation of
decision problems; Bayes Law and Bayesian
networks; value of information; utility theory;
risk sharing and decisions; case studies.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2015-2016 |
Decision Analysis |
3 |
| Spring 2009-2010 |
Decision Analysis |
3 |
| Spring 2001-2002 |
Decision Analysis |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 524 System Simulation |
3 Credits |
|
Modeling and analysis of production and service systems
through the use of discrete-event simulation; world
views in simulation; input modeling; random number and
variate generation; output analysis; verification and
validation issues.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Fall 2017-2018 |
System Simulation |
3 |
| Spring 2005-2006 |
System Simulation |
3 |
| Spring 2000-2001 |
System Simulation |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 525 Operations Research and Data Mining |
3 Credits |
|
The course will address unsupervised learning, supervised
learning, association rule mining and feature subset
selection problems, focus on the optimization formulations
of these problems, discuss various techniques proposed as
solutions and present their implementation particularly in
the context of operations management. Among others,
probabilistic and statistical methods, possibilistic methods
clustering algorithms, decision trees, metaheuristics (such
as genetic algorithms, simulated annealing, etc.) and
mathematical programming will be covered as part of the
toolbox that are widely utilized in data mining. As part of
the course multi criteria decision making and multi
objective optimization, and their usage in data mining will
also be covered. The course will include case studies from
both manufacturing and service industries.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2023-2024 |
Operations Research and Data Mining |
3 |
| Spring 2022-2023 |
Operations Research and Data Mining |
3 |
| Fall 2021-2022 |
Operations Research and Data Mining |
3 |
| Fall 2019-2020 |
Operations Research and Data Mining |
3 |
| Fall 2018-2019 |
Operations Research and Data Mining |
3 |
| Fall 2016-2017 |
Operations Research and Data Mining |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 527 System Dynamics |
3 Credits |
|
Systems thinking and the system dynamics worldview;
methods to elicit and map the structure of complex
systems and relate those structures to their dynamics;
tools for modeling and simulation of complex systems;
applications including corporate growth and stagnation,
the diffusion of new technologies, business cycles, the
use and reliability of forecasts, the design of supply
chains, service quality management, project management and
product development, the dynamics of infectious diseases.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Fall 2019-2020 |
System Dynamics |
3 |
| Spring 2016-2017 |
System Dynamics |
3 |
| Fall 2014-2015 |
System Dynamics |
3 |
| Spring 2012-2013 |
System Dynamics |
3 |
| Spring 2010-2011 |
System Dynamics |
3 |
| Spring 2007-2008 |
System Dynamics |
3 |
| Fall 2005-2006 |
System Dynamics |
3 |
| Fall 2003-2004 |
System Dynamics |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 530 Logistics and Transportation Systems Planning |
3 Credits |
|
The course aims at giving the students a solid
understanding of mathematical modeling approaches,
analytical tools and techniques that are useful in the
design and planning of logistics and transportation
systems. The topics include logistics network design,
facility location and allocation, long- and short-haul
transportation, vehicle routing and scheduling problems
as well as issues related to sustainable mobility. We will
discuss the theory, application methods, and techniques
that are needed to successfully model, analyze, and solve
these problems. We will develop and employ both exact
and approximate methods to solve problems arising in
logistics and transportation systems, and implement
computerized applications. The course is designed for
graduate students who have a solid background in
mathematical programming and are proficient in coding.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2022-2023 |
Logistics and Transportation Systems Planning |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 532 Stochastic Models in Finance |
3 Credits |
|
The objective of the course is to introduce
basic stochastic models and techniques used in
mathematical finance. The first half of the course
is dedicated to discrete-time models,
the other half to their continuous-time counterparts.
The topics covered include pricing and hedging in binomial
models and Black-Scholes models, fundamental theorems
of asset pricing, martingales, Brownian motion, stochastic
integration, Itô rule. Depending on the progress in
class, we also briefly discuss SDE’s as they appear in
continuous-time models.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Fall 2023-2024 |
Stochastic Models in Finance |
3 |
| Fall 2013-2014 |
Stochastic Models in Finance |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 536 Monte Carlo Methods in Finance |
3 Credits |
|
The course aims to introduce the Monte
Carlo methods and techniques used in
mathematical finance. In this field, many
problems involve computing expectations.
Pricing various derivatives, computing
default/ruin probabilities, finding
optimal/well-performing portfolios are
some well-known examples of such
problems. In the course, after discussing
the basics of probability and simulation, we
learn how Monte Carlo methods apply to
these problems.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2023-2024 |
Monte Carlo Methods in Finance |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 545 Production Systems Planning and Design |
3 Credits |
|
Study of optimization models for planning and design of
production systems. Emphasis is given to models used for
decision making at strategic and tactical levels. Topics
include forecasting, facility location, capacity planning,
production control and inventory planning.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Fall 2015-2016 |
Production Systems Planning and Design |
3 |
| Spring 2004-2005 |
Production Systems Planning and Design |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 550 Sequencing and Scheduling |
3 Credits |
|
Analysis and solution of sequencing and scheduling
problems; complexity theory and computational analysis of
sequencing and scheduling algorithms; exact and heuristic
solution procedures for single machine problems; scheduling
of job shops, flow shops and flexible manufacturing systems;
scheduling of parallel processors.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2011-2012 |
Sequencing and Scheduling |
3 |
| Spring 2009-2010 |
Sequencing and Scheduling |
3 |
| Spring 2008-2009 |
Sequencing and Scheduling |
3 |
| Fall 2000-2001 |
Sequencing and Scheduling |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 551 Graduate Seminar I |
0 Credit |
|
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2023-2024 |
Graduate Seminar I |
0 |
| Spring 2022-2023 |
Graduate Seminar I |
0 |
| Fall 2022-2023 |
Graduate Seminar I |
0 |
| Spring 2021-2022 |
Graduate Seminar I |
0 |
| Fall 2021-2022 |
Graduate Seminar I |
0 |
| Spring 2020-2021 |
Graduate Seminar I |
0 |
| Fall 2020-2021 |
Graduate Seminar I |
0 |
| Spring 2019-2020 |
Graduate Seminar I |
0 |
| Fall 2019-2020 |
Graduate Seminar I |
0 |
| Spring 2018-2019 |
Graduate Seminar I |
0 |
| Fall 2018-2019 |
Graduate Seminar I |
0 |
| Spring 2017-2018 |
Graduate Seminar I |
0 |
| Fall 2017-2018 |
Graduate Seminar I |
0 |
| Spring 2016-2017 |
Graduate Seminar I |
0 |
| Fall 2016-2017 |
Graduate Seminar I |
0 |
| Spring 2015-2016 |
Graduate Seminar I |
0 |
| Fall 2015-2016 |
Graduate Seminar I |
0 |
| Spring 2014-2015 |
Graduate Seminar I |
0 |
| Fall 2014-2015 |
Graduate Seminar I |
0 |
| Fall 2013-2014 |
Graduate Seminar I |
0 |
| Fall 2012-2013 |
Graduate Seminar I |
0 |
| Fall 2011-2012 |
Graduate Seminar I |
0 |
| Fall 2010-2011 |
Graduate Seminar I |
0 |
| Summer 2009-2010 |
Graduate Seminar I |
0 |
| Fall 2009-2010 |
Graduate Seminar I |
0 |
| Fall 2008-2009 |
Graduate Seminar I |
0 |
| Fall 2007-2008 |
Graduate Seminar I |
0 |
| Fall 2006-2007 |
Graduate Seminar I |
0 |
| Fall 2005-2006 |
Graduate Seminar I |
0 |
| Fall 2004-2005 |
Graduate Seminar I |
0 |
| Fall 2003-2004 |
Graduate Seminar I |
0 |
| Fall 2002-2003 |
Graduate Seminar I |
0 |
| Fall 2001-2002 |
Graduate Seminar I |
0 |
| Fall 2000-2001 |
Graduate Seminar I |
0 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 1 ECTS (1 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 552 Graduate Seminar II |
0 Credit |
|
|
| Last Offered Terms |
Course Name |
SU Credit |
| Fall 2023-2024 |
Graduate Seminar II |
0 |
| Spring 2022-2023 |
Graduate Seminar II |
0 |
| Fall 2022-2023 |
Graduate Seminar II |
0 |
| Spring 2021-2022 |
Graduate Seminar II |
0 |
| Fall 2021-2022 |
Graduate Seminar II |
0 |
| Spring 2020-2021 |
Graduate Seminar II |
0 |
| Fall 2020-2021 |
Graduate Seminar II |
0 |
| Spring 2019-2020 |
Graduate Seminar II |
0 |
| Fall 2019-2020 |
Graduate Seminar II |
0 |
| Spring 2018-2019 |
Graduate Seminar II |
0 |
| Fall 2018-2019 |
Graduate Seminar II |
0 |
| Spring 2017-2018 |
Graduate Seminar II |
0 |
| Fall 2017-2018 |
Graduate Seminar II |
0 |
| Spring 2016-2017 |
Graduate Seminar II |
0 |
| Fall 2016-2017 |
Graduate Seminar II |
0 |
| Spring 2015-2016 |
Graduate Seminar II |
0 |
| Fall 2015-2016 |
Graduate Seminar II |
0 |
| Spring 2014-2015 |
Graduate Seminar II |
0 |
| Spring 2013-2014 |
Graduate Seminar II |
0 |
| Spring 2012-2013 |
Graduate Seminar II |
0 |
| Spring 2011-2012 |
Graduate Seminar II |
0 |
| Spring 2010-2011 |
Graduate Seminar II |
0 |
| Spring 2009-2010 |
Graduate Seminar II |
0 |
| Spring 2008-2009 |
Graduate Seminar II |
0 |
| Spring 2007-2008 |
Graduate Seminar II |
0 |
| Spring 2006-2007 |
Graduate Seminar II |
0 |
| Spring 2005-2006 |
Graduate Seminar II |
0 |
| Spring 2004-2005 |
Graduate Seminar II |
0 |
| Spring 2003-2004 |
Graduate Seminar II |
0 |
| Spring 2002-2003 |
Graduate Seminar II |
0 |
| Spring 2001-2002 |
Graduate Seminar II |
0 |
| Spring 2000-2001 |
Graduate Seminar II |
0 |
|
| Prerequisite: IE 551 - Doctorate - Min Grade D |
| or IE 551 - Masters - Min Grade D |
| Corequisite: __ |
| ECTS Credit: 1 ECTS (1 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 553 Facility Design and Analysis |
3 Credits |
|
Product/process analysis; technology selection; facility
location; production and service facilities layout; material
handling systems, storage systems, mathematical programming
models and methods for location and layout problems.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2023-2024 |
Facility Design and Analysis |
3 |
| Spring 2019-2020 |
Facility Design and Analysis |
3 |
| Fall 2012-2013 |
Facility Design and Analysis |
3 |
| Fall 2010-2011 |
Facility Design and Analysis |
3 |
| Fall 2008-2009 |
Facility Design and Analysis |
3 |
| Spring 2007-2008 |
Facility Design and Analysis |
3 |
| Fall 2003-2004 |
Facility Design and Analysis |
3 |
| Fall 2002-2003 |
Facility Design and Analysis |
3 |
| Fall 2001-2002 |
Facility Design and Analysis |
3 |
| Fall 2000-2001 |
Facility Design and Analysis |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 554 Supply Chain Management |
3 Credits |
|
Supply chain characterization; replenishment management
and supplier relations; aggregate production planning;
lot sizing; lead time management; material and capacity
requirements planning; master production and operations
scheduling; pull production systems; manufacturing
inventories; storage management; distribution planning;
vehicle routing; demand management; use of ERP software;
web based approaches; case studies.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2012-2013 |
Supply Chain Management |
3 |
| Spring 2011-2012 |
Supply Chain Management |
3 |
| Spring 2009-2010 |
Supply Chain Management |
3 |
| Spring 2008-2009 |
Supply Chain Management |
3 |
| Spring 2007-2008 |
Supply Chain Management |
3 |
| Spring 2006-2007 |
Supply Chain Management |
3 |
| Spring 2005-2006 |
Supply Chain Management |
3 |
| Spring 2004-2005 |
Supply Chain Management |
3 |
| Spring 2003-2004 |
Supply Chain Management |
3 |
| Spring 2002-2003 |
Supply Chain Management |
3 |
| Spring 2001-2002 |
Supply Chain Management |
3 |
| Spring 2000-2001 |
Supply Chain Management |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 567 Manufacturing Systems Modelling |
3 Credits |
|
Hierarchical design, planning, and control of
manufacturing systems; assembly lines; automated
transfer lines; cellular manufacturing; flexible
manufacturing systems; facility location and layout.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2019-2020 |
Manufacturing Systems Modelling |
3 |
| Spring 2017-2018 |
Manufacturing Systems Modelling |
3 |
| Spring 2010-2011 |
Manufacturing Systems Modelling |
3 |
| Fall 2009-2010 |
Manufacturing Systems Modelling |
3 |
| Fall 2007-2008 |
Manufacturing Systems Modelling |
3 |
| Spring 2006-2007 |
Manufacturing Systems Modelling |
3 |
| Spring 2005-2006 |
Manufacturing Systems Modelling |
3 |
| Fall 2004-2005 |
Manufacturing Systems Modelling |
3 |
| Fall 2003-2004 |
Manufacturing Systems Modelling |
3 |
| Fall 2002-2003 |
Manufacturing Systems Modelling |
3 |
| Fall 2001-2002 |
Manufacturing Systems Modelling |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 58000 Special Topics in IE: Logistics and Transportation Planning |
3 Credits |
|
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2018-2019 |
Special Topics in IE: Logistics and Transportation Planning |
3 |
| Fall 2016-2017 |
Special Topics in IE: Logistics and Transportation Planning |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 58001 Special Topics in IE: Simulation for Statistical Inference |
3 Credits |
|
|
| Last Offered Terms |
Course Name |
SU Credit |
| Fall 2016-2017 |
Special Topics in IE: Simulation for Statistical Inference |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 58002 Special Topics in IE: Production Planning |
3 Credits |
|
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2016-2017 |
Special Topics in IE: Production Planning |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 58004 Special Topics in IE: Applications of Combinatorial Optimization |
3 Credits |
|
Applications of graph theory, graph coloring,
introduction to approximation algorithms, Boolean modeling
and optimization, quadratic functions, Horn functions
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2019-2020 |
Special Topics in IE: Applications of Combinatorial Optimization |
3 |
|
| Prerequisite: (IE 501 - Doctorate - Min Grade D |
| or IE 501 - Masters - Min Grade D) |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 58005 Special Topics in IE: Advanced statistics with R |
3 Credits |
|
The course aims to discuss importance topics in
statistics in a mathematically rigorous way. The
topics that will be discussed include sampling
distributions and asymptotics, point and interval
estimations, hypothesis testing, ANOVA and
regression analysis. Implementations will be
illustrated with R.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Fall 2022-2023 |
Special Topics in IE: Advanced statistics with R |
3 |
| Fall 2020-2021 |
Special Topics in IE: Advanced statistics with R |
3 |
| Fall 2019-2020 |
Special Topics in IE: Advanced statistics with R |
3 |
| Fall 2018-2019 |
Special Topics in IE: Advanced statistics with R |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 590 Master Thesis |
0 Credit |
|
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2023-2024 |
Master Thesis |
0 |
| Fall 2023-2024 |
Master Thesis |
0 |
| Spring 2022-2023 |
Master Thesis |
0 |
| Fall 2022-2023 |
Master Thesis |
0 |
| Spring 2021-2022 |
Master Thesis |
0 |
| Fall 2021-2022 |
Master Thesis |
0 |
| Spring 2020-2021 |
Master Thesis |
0 |
| Fall 2020-2021 |
Master Thesis |
0 |
| Spring 2019-2020 |
Master Thesis |
0 |
| Fall 2019-2020 |
Master Thesis |
0 |
| Spring 2018-2019 |
Master Thesis |
0 |
| Fall 2018-2019 |
Master Thesis |
0 |
| Spring 2017-2018 |
Master Thesis |
0 |
| Fall 2017-2018 |
Master Thesis |
0 |
| Spring 2016-2017 |
Master Thesis |
0 |
| Fall 2016-2017 |
Master Thesis |
0 |
| Spring 2015-2016 |
Master Thesis |
0 |
| Fall 2015-2016 |
Master Thesis |
0 |
| Spring 2014-2015 |
Master Thesis |
0 |
| Fall 2014-2015 |
Master Thesis |
0 |
| Spring 2013-2014 |
Master Thesis |
0 |
| Fall 2013-2014 |
Master Thesis |
0 |
| Spring 2012-2013 |
Master Thesis |
0 |
| Fall 2012-2013 |
Master Thesis |
0 |
| Spring 2011-2012 |
Master Thesis |
0 |
| Fall 2011-2012 |
Master Thesis |
0 |
| Spring 2010-2011 |
Master Thesis |
0 |
| Fall 2010-2011 |
Master Thesis |
0 |
| Spring 2009-2010 |
Master Thesis |
0 |
| Fall 2009-2010 |
Master Thesis |
0 |
| Spring 2008-2009 |
Master Thesis |
0 |
| Fall 2008-2009 |
Master Thesis |
0 |
| Spring 2007-2008 |
Master Thesis |
0 |
| Fall 2007-2008 |
Master Thesis |
0 |
| Spring 2006-2007 |
Master Thesis |
0 |
| Fall 2006-2007 |
Master Thesis |
0 |
| Spring 2005-2006 |
Master Thesis |
0 |
| Fall 2005-2006 |
Master Thesis |
0 |
| Spring 2004-2005 |
Master Thesis |
0 |
| Fall 2004-2005 |
Master Thesis |
0 |
| Spring 2003-2004 |
Master Thesis |
0 |
| Fall 2003-2004 |
Master Thesis |
0 |
| Spring 2002-2003 |
Master Thesis |
0 |
| Fall 2002-2003 |
Master Thesis |
0 |
| Spring 2001-2002 |
Master Thesis |
0 |
| Fall 2001-2002 |
Master Thesis |
0 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 50 ECTS (50 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 592 Project Course |
0 Credit |
|
All graduate students pursuing a non-thesis M.Sc. Program
are required to complete a project. The project
topic and contents are based on the interest and
background of the student and are approved by the
faculty member serving as the project supervisor. At the
completion of the project, the student is required to submit
a final report. The final report is to be approved by the
project supervisor.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Fall 2010-2011 |
Project Course |
0 |
| Fall 2009-2010 |
Project Course |
0 |
| Fall 2008-2009 |
Project Course |
0 |
| Fall 2007-2008 |
Project Course |
0 |
| Fall 2005-2006 |
Project Course |
0 |
| Fall 2004-2005 |
Project Course |
0 |
| Fall 2003-2004 |
Project Course |
0 |
| Fall 2002-2003 |
Project Course |
0 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 20 ECTS (20 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 601 Optimization Theory |
3 Credits |
|
Convex optimization and functional analysis; theory of
duality; iterative methods and convergence proofs;
interior point methods for linear programming;
computational complexity of mathematical
programming problems; extensions of linear programming.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2021-2022 |
Optimization Theory |
3 |
| Fall 2019-2020 |
Optimization Theory |
3 |
| Spring 2017-2018 |
Optimization Theory |
3 |
|
| Prerequisite: (IE 501 - Masters - Min Grade D) |
| or (IE 501 - Doctorate - Min Grade D) |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 602 Stochastic Programming |
3 Credits |
|
Stochastic programming is one of the fundamental
approaches that can be used to model
decision-making under uncertainty. It is concerned with the
mathematical programming problems, where the uncertain
problem parameters are represented by random variables,
and it extends deterministic optimization by explicitly
accounting for the uncertainty already in the modeling
age. This course will provide a broad overview
of the main themes and methods of the subject.
This course covers various optimization models
(chance-constrained optimization, two-stage
stochastic programming models, optimization with risk
measures, etc.), as well as their mathematical
programming-based solution methods and applications to
practical problems. Since stochastic programs are
computationally challenging, there is a particular
emphasis in this course on algorithmic tools (especially,
on decomposition-based algorithms) for
solving large-scale instances.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2016-2017 |
Stochastic Programming |
3 |
|
| Prerequisite: IE 501 - Doctorate - Min Grade D |
| or IE 501 - Masters - Min Grade D |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 604 Integer Programming |
3 Credits |
|
In this course, the students will learn the
mathematics of discrete optimization including
the representation of problems by mathematical
models and the solution of these models. In
computational complexity part, the concepts of
polynomial computation and NP-completeness
will be introduced, and equivalence of separation
and optimization will be discussed. Then, basic
approaches and algorithms for solving discrete
optimization problems will be introduced. The
branch-and-bound algorithm, the theory of valid
inequalities, and the results known for simplest
discrete sets that are necessary to understand the
cutting planes generated by today’s commercial
solvers will be covered. In polyhedral theory, the
concepts of facets of polyhedra and the idea of
representing the convex hull of a discrete set of
points will be covered. Extended formulations
and the reformulations that enable decomposition
algorithms will be addressed.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2022-2023 |
Integer Programming |
3 |
| Spring 2020-2021 |
Integer Programming |
3 |
|
| Prerequisite: IE 501 - Masters - Min Grade D |
| or IE 501 - Doctorate - Min Grade D |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 605 Advanced Topics in Stochastic Processes |
3 Credits |
|
Stochastic modelling and optimization; decomposition
coordination algorithms for large-scale mathematical
programming; and applications in
stochastic programming; An advanced discussion
of a subject in applied probability with significant
interest to engineering, e.g stochastic inventory
control and scheduling; performance evaluation
in stochastic systems. Individual projects in stochastic
modeling.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2014-2015 |
Advanced Topics in Stochastic Processes |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 606 Large Scale Optimization |
3 Credits |
|
Design of efficient algorithms that exploit the
structure of large scale optimization problems. Relaxation;
decomposition; sparse systems; simplex with
bounded variables; cutting plane methods and
heuristic algorithms; effective computation techniques
for real life applications.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2023-2024 |
Large Scale Optimization |
3 |
| Spring 2018-2019 |
Large Scale Optimization |
3 |
| Spring 2015-2016 |
Large Scale Optimization |
3 |
| Spring 2004-2005 |
Large Scale Optimization |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 640 Behavioral and Experimental Methods in Operations Management |
3 Credits |
|
This course aims to introduce the use of behavioral and
experimental methods that have been increasingly popular in
the field of operations management. In particular
we use a supply chain scenario to study how human beings
make individual and strategic decisions in the
face of uncertainty and risk.
First, we use the standard newsvendor problem
to discuss decisions involving only a single individual.
This problem is concerned with the order quantity decision
of a retailer that faces probabilistic demand.
Then, we consider a simple manufacturer-retailer
supply chain where the retailer faces the newsvendor
problem, and her problem parameters are determined by
the contract that the manufacturer offers. This scenario
allows us to study what happens to decisions when two
individuals interact strategically with each other
.
Course discussion is based on results from decision-making
experiments with human subjects. In addition to published
research papers, we also use data from experiments conducted
at Sabanci University.
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2021-2022 |
Behavioral and Experimental Methods in Operations Management |
3 |
| Spring 2020-2021 |
Behavioral and Experimental Methods in Operations Management |
3 |
| Fall 2017-2018 |
Behavioral and Experimental Methods in Operations Management |
3 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 10 ECTS (10 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 751 Graduate Seminar I |
0 Credit |
|
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2023-2024 |
Graduate Seminar I |
0 |
| Spring 2022-2023 |
Graduate Seminar I |
0 |
| Fall 2022-2023 |
Graduate Seminar I |
0 |
| Spring 2021-2022 |
Graduate Seminar I |
0 |
| Fall 2021-2022 |
Graduate Seminar I |
0 |
| Fall 2020-2021 |
Graduate Seminar I |
0 |
| Spring 2019-2020 |
Graduate Seminar I |
0 |
| Fall 2019-2020 |
Graduate Seminar I |
0 |
| Fall 2018-2019 |
Graduate Seminar I |
0 |
| Spring 2017-2018 |
Graduate Seminar I |
0 |
| Fall 2017-2018 |
Graduate Seminar I |
0 |
| Fall 2016-2017 |
Graduate Seminar I |
0 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 1 ECTS (1 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 752 Graduate Seminar II |
0 Credit |
|
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2022-2023 |
Graduate Seminar II |
0 |
| Fall 2022-2023 |
Graduate Seminar II |
0 |
| Spring 2021-2022 |
Graduate Seminar II |
0 |
| Spring 2020-2021 |
Graduate Seminar II |
0 |
| Fall 2020-2021 |
Graduate Seminar II |
0 |
| Spring 2019-2020 |
Graduate Seminar II |
0 |
| Spring 2018-2019 |
Graduate Seminar II |
0 |
| Fall 2018-2019 |
Graduate Seminar II |
0 |
| Spring 2017-2018 |
Graduate Seminar II |
0 |
| Spring 2016-2017 |
Graduate Seminar II |
0 |
|
| Prerequisite: IE 751 - Masters - Min Grade D |
| or IE 751 - Doctorate - Min Grade D |
| Corequisite: __ |
| ECTS Credit: 1 ECTS (1 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
| IE 790 Ph.D. Dissertation |
0 Credit |
|
|
| Last Offered Terms |
Course Name |
SU Credit |
| Spring 2023-2024 |
Ph.D. Dissertation |
0 |
| Fall 2023-2024 |
Ph.D. Dissertation |
0 |
| Spring 2022-2023 |
Ph.D. Dissertation |
0 |
| Fall 2022-2023 |
Ph.D. Dissertation |
0 |
| Spring 2021-2022 |
Ph.D. Dissertation |
0 |
| Fall 2021-2022 |
Ph.D. Dissertation |
0 |
| Spring 2020-2021 |
Ph.D. Dissertation |
0 |
| Fall 2020-2021 |
Ph.D. Dissertation |
0 |
| Spring 2019-2020 |
Ph.D. Dissertation |
0 |
| Fall 2019-2020 |
Ph.D. Dissertation |
0 |
| Spring 2018-2019 |
Ph.D. Dissertation |
0 |
| Fall 2018-2019 |
Ph.D. Dissertation |
0 |
| Spring 2017-2018 |
Ph.D. Dissertation |
0 |
| Fall 2017-2018 |
Ph.D. Dissertation |
0 |
| Spring 2016-2017 |
Ph.D. Dissertation |
0 |
| Fall 2016-2017 |
Ph.D. Dissertation |
0 |
| Spring 2015-2016 |
Ph.D. Dissertation |
0 |
| Fall 2015-2016 |
Ph.D. Dissertation |
0 |
| Spring 2014-2015 |
Ph.D. Dissertation |
0 |
| Fall 2014-2015 |
Ph.D. Dissertation |
0 |
| Spring 2013-2014 |
Ph.D. Dissertation |
0 |
| Fall 2013-2014 |
Ph.D. Dissertation |
0 |
| Spring 2012-2013 |
Ph.D. Dissertation |
0 |
| Fall 2012-2013 |
Ph.D. Dissertation |
0 |
| Spring 2011-2012 |
Ph.D. Dissertation |
0 |
| Fall 2011-2012 |
Ph.D. Dissertation |
0 |
| Spring 2010-2011 |
Ph.D. Dissertation |
0 |
| Fall 2010-2011 |
Ph.D. Dissertation |
0 |
| Spring 2009-2010 |
Ph.D. Dissertation |
0 |
| Fall 2009-2010 |
Ph.D. Dissertation |
0 |
| Spring 2008-2009 |
Ph.D. Dissertation |
0 |
| Fall 2008-2009 |
Ph.D. Dissertation |
0 |
| Spring 2007-2008 |
Ph.D. Dissertation |
0 |
| Fall 2007-2008 |
Ph.D. Dissertation |
0 |
| Spring 2006-2007 |
Ph.D. Dissertation |
0 |
| Fall 2006-2007 |
Ph.D. Dissertation |
0 |
| Spring 2005-2006 |
Ph.D. Dissertation |
0 |
| Fall 2005-2006 |
Ph.D. Dissertation |
0 |
|
| Prerequisite: __ |
| Corequisite: __ |
| ECTS Credit: 180 ECTS (180 ECTS for students admitted before 2013-14 Academic Year) |
| General Requirements: |
|
|
| |
