Master of Science in Industrial Engineering
Curriculum
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Required Courses: All students have to take the
following 2 courses.
- INDR 501 Optimization Models and Algorithms
- INDR 503 Stochastic Models and Their Applications
- Elective Courses: All students have to take 5
of the following elective courses according to their research
interests and thesis subjects to complete at least 15 credits. All
courses have 3 credits unless otherwise specified.
- INDR 502 Logistics and Supply Chain Systems
- INDR 504 Advanced Engineering Materials Manufacturing
- INDR 505 Manufacturing Systems
- INDR 506 Computer Integrated Manufacturing and Automation
- INDR 508 Discrete Event Simulation
- INDR 520 Network Models and Optimization
- INDR 530 Decision Analysis
- INDR 551 Advanced Optimization Methods
- INDR 553 Advanced Stochastic Processes
- INDR 562 Integer and Combinatorial Optimization
- INDR 566 Scheduling
- INDR 568 Heuristic Methods
- INDR 578 Advanced Models in Supply Chain Management (Crosslisting with OPSM 602)
- INDR 580 Selected Topics in Industrial Engineering
- INDR 583 Supply Chain
Modeling and Analysis
- INDR 584 Logistics Management
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- OPSM 502 Operations Management
- OPSM 602 Advanced Models in Supply Chain Management (Crosslisting with INDR 578)
- OPSM 632 Introduction to Management Science
- OPSM 636 Service Operations Management
- OPSM 637 Operations Strategy
- OPSM 638 Supply Chain Management
- OPSM 639 Project Management
- OPSM 650 Selected Topics: Manufacturing and Service Op. Strategy
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- MGIS 501 Introduction to Management Information Systems
- MGIS 641 Database Management Systems
- MGIS 650 Selected Topics in Operations Management
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- ECOE 554 Machine Learning
- Courses which are not listed above can be taken with the
suggestion and permission of the program coordinator and/or
thesis advisor. In addition to the course load, students
have to take a seminar course and complete their M.S.
thesis. For this purpose, they register to the following
courses.
- INDR 590 Seminar
- INDR 595 M.S. Thesis
Course Descriptions
- INDR 501 Optimization Models and
Algorithms (3 Credits)
- Convex analysis, optimality conditions, linear
programming model formulation, simplex method, duality,
dual simplex method, sensitivity analysis; assignment,
transportation, and transshipment problems.
- Prerequisite: An undergraduate
level Operations Research course or consent of the
instructor.
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- INDR 502 Logistics and Supply Chain
Systems (3 Credits)
- Introduction to the concepts and terminology of
logistics and supply chain management. Examination of
components of logistics and supply chain systems such as
purchasing, storage, production, inventory, and
transportation systems. Analysis of interactions and
trade-offs among these components using mathematical
models and quantitative techniques.
- Prerequisite: INDR 501 or consent
of the instructor.
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- INDR 503 Stochastic Models and
Their Applications (3 Credits)
- The basic theory of the Poisson process, renewal
processes, Markov chains in discrete and continuous
time, as well as Brownian motion and random walks are
developed. Applications of these stochastic processes
are emphasized by examples, which are drawn from
inventory and queueing theory, reliability and
replacement theory, finance, population dynamics and
other biological models.
- Prerequisite: An undergraduate
level statistics course or consent of the instructor.
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- INDR 504 Advanced Engineering
Materials Manufacturing (3 Credits)
- Advanced Engineering Material Manufacturing
Processes will be studied for (i) metals and (ii)
plastics and composites. Material removal, addition, and
change of form processes will be studied for metals. In
the plastics and composites part,
similarities/differences, advantages/disadvantages, and
proper selection of manufacturing processes such as
Injection Molding, Compression Molding, Extrusion, Sheet
Forming, Tow Placement, Pultrusion, Liquid Molding,
Filament Winding, Pultrusion and Autoclave Processing
will be illustrated with applications from aerospace,
automotive, biomedical, sporting goods and civil
infrastructure industries. Issues and their solutions
with in-site sensing and on- and off-line control will
be studied with examples.
- Prerequisite: INDR 505 or consent
of the instructor.
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- INDR 505 Manufacturing Systems (3
Credits)
- This course will cover the basic concepts and
techniques in hierarchical design, planning, and control
of manufacturing systems. Topics include flow line and
assembly systems, group technology and cellular
manufacturing, just-in-time, flexible manufacturing
systems.
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- INDR 506 Computer Integrated
Manufacturing and Automation (3 Credits)
- This course introduces Computer Aided Design and
Manufacturing (CAD/CAM) Systems, Computer Numerical
Control (CNC) Machine Tools, Modern Sensors in
Manufacturing, Machining Processes, Rapid Prototyping,
and Fundamentals of Industrial Robotics.
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- INDR 508 Discrete Event Simulation
(3 Credits)
- Topics on distribution fitting and generating random
numbers and random variates will be covered as well as
the statistical analysis of simulation output including
some well-known analysis methods and variance reduction
techniques. Recent developments in the area will also be
discussed.
- Prerequisite: INDR 503 or consent
of the instructor.
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- INDR 520 Network Models and
Optimization (3 Credits)
- Network flow models and optimization problems.
Algorithms and applications. Minimum spanning tree
problem. Shortest path problems. Maximum flow problems,
minimum cuts in undirected graphs and cut-trees. The
minimum cost network flow problem. Matching problems.
Generalized flows. Multicommodity flows and solution by
Lagrangean relaxation, column generation and
Dantzig-Wolfe decomposition. Network design problems
including the Steiner tree problem and the
multicommodity capacitated network design problem;
formulations, branch-and-cut approaches and
approximation algorithms.
- Prerequisite: INDR 262 or consent
of the instructor.
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- INDR 530 Decision Analysis (3
Credits)
- Tools, techniques, and skills needed to analyze
decision-making problems characterized by uncertainty,
risk, and conflicting objectives. Methods for
structuring and modeling decision problems and
applications to problems in a variety of managerial
decision-making contexts. Structuring decision problems:
Decision trees, model building, solution methods and
sensitivity analysis; Bayes' rule, the value of
information and using decision analysis software.
Uncertainty and its measurement: Probability assessment.
Utility Theory: Risk attitudes, single- and
multi-attribute utility theory, and risk management.
Decision making with multiple objectives.
- Prerequisite: ENG 200 or consent of
instructor.
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- INDR 566 Scheduling (3 Credits)
- Introduction to scheduling: examples of scheduling
problems, role of scheduling, terminology, concepts,
classifications; solution methods: enumerative methods,
heuristic and approximation algorithms; single machine
completion time, lateness and tardiness models; single
machine sequence dependent setup models; parallel
machine models; flow-shop models; flexible flow-shop
models; job-shop models; shifting bottleneck heuristic;
open-shop models; models in computer systems; survey of
other scheduling problems; advanced concepts.
- Prerequisite: Consent of
instructor.
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- INDR 551 Advanced Optimization
Methods (3 Credits)
- Combinatorial optimization, structure of integer
programs, pure integer and mixed integer programming
problems, branch and bound methods, cutting plane and
polyhedral approach, convexity, local and global optima,
Newton-type, and conjugate gradient methods for
unconstrained optimization, Karush-Kuhn-Tucker
conditions for optimality, algorithms for constrained
nonlinear programming problems, applications in
combinatorial and nonlinear optimization.
- Prerequisite: INDR 501 or consent
of the instructor.
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- INDR 553 Advanced Stochastic
Processes (3 Credits)
- Brief review of basic processes like Poisson,
Markov and renewal processes; Markov renewal processes
and theory, regenerative and semi-regenerative
processes; random walk, Wiener process and Brownian
motion; martingales; stochastic differential equations
and integrals; applications in queueing, inventory,
reliability and financial systems.
- Prerequisite: INDR 503 or consent
of the instructor.
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- INDR 562 Integer and Combinatorial Optimization (3 Credits)
- This course covers the models and theory of integer and
combinatorial optimization problems. The theory and
properties of solution spaces for integer and combinatorial
optimization problems will be covered.
- Prerequisite: INDR 501 or consent
of the instructor.
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- INDR 568 Heuristic Methods (3
Credits)
- Constructive heuristics; improving heuristics;
metaheuristics: simulated annealing, genetic algorithms,
tabu search, scatter search, path relinking, ant colony
optimization, variable neighborhood search, and their
hybrids; heuristic methods based on relaxation and
decomposition; applications: routing, scheduling,
cutting and packing, inventory and production
management, location, assignment of resources,
bioinformatics, and telecommunications.
- Prerequisite: INDR 501 or consent
of the instructor.
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- INDR 578 Advanced Models in Supply
Chain Management (3 Credits)
- Dynamic inventory policies for single-stage
inventory systems: concepts of optimality and optimal
policies. Multi-Echelon Systems: uncapacitated models
and optimal policies, capacitated models: different
control mechanisms. Multiple locations and multiple
items: inventory and capacity allocation. Decentralized
control and the effects of competition on the supply
chain: coordination and contracting issues.
- Prerequisite: INDR 503, INDR 505 or
consent of the instructor.
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- INDR 583 Supply Chain Modeling and Analysis
(3 Credits)
- Application and development of mathematical modeling
tools for the analysis of strategic, tactical, and
operational supply-chain problems. Mathematical
programming formulations for integrated planning of
capacity and demand in a supply chain. Planning and
managing inventories in multi-level systems, centralized
versus decentralized control of supply chain
inventories. Models and algorithms for transportation
and logistics systems design and analysis. Supply chain
coordination issues and achieving coordination through
contracts. The role of information technology and
enterprise resource planning (ERP) and Advanced Planning
and Optimization software.
- Prerequisite: (ENGR. 200 and INDR.
262 and INDR. 372) or consent of the instructor
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- INDR 584 Logistics Management
(3 Credits)
- Introduction to logistics systems; logistics
network design, location models; warehouse design,
tactical decisions, operational decisions;
transportation management; planning and managing freight
transportation; fleet management, vehicle routing
problem.
- Prerequisite: INDR. 262
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- INDR/OPSM 590 Seminar (3
Credits)
- A series of lectures given by faculty or outside
speakers. Participating students must also make
presentations during the semester.
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- INDR 591 Project (3 Credits)
- Independent research towards M.S. degree without
thesis option.
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- INDR 595 M.S. Thesis (3 Credits)
- Independent research towards M.S. degree with thesis
option.
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- INDR 596 Ph.D. Thesis (3 Credits)
- Independent research towards Ph.D. degree.
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- OPSM 502 Operations Management (3
Credits)
- Fundamental decisions and tradeoffs in control of a
firm’s operations: obtaining and controlling the flow of
materials through a production facility and distributing
them to customers. Four modules: process fundamentals;
cross functional integration, coordination, and control;
improving the performance of productive systems; and
competing through technology and operations.
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- OPSM 602 Advanced Models in Supply
Chain Management (3 Credits)
- Dynamic inventory policies for single-stage
inventory systems: concepts of optimality and optimal
policies. Multi-Echelon Systems: uncapacitated models
and optimal policies, capacitated models: different
control mechanisms. Multiple locations and multiple
items: inventory and capacity allocation. Decentralized
control and the effects of competition on the supply
chain: coordination and contracting issues.
- Prerequisite: INDR 503, INDR 505 or
consent of the instructor.
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- QMBU 632 Introduction to Management
Science (3 Credits)
- Fundamental quantitative methods used in business
decision-making: mathematical programming, stochastic
modeling, and simulation, with emphasis on formulation,
analysis, and implementation.
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- OPSM 637 Operations Strategy (3
Credits)
- Coordination of marketing, operations, and finance
functions within a framework designed to meet the
competitive requirements of the marketplace. Interface
issues between corporate strategy and the management of
the operations function.
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- OPSM 638 Supply Chain Management (3
Credits)
- Process-oriented, integrated approach to procuring,
producing, and delivering products and services to
customers. Strategic and operational issues, such as
sharing information and joint planning, reduction in
supplier base, channel-wide inventory management,
channel-wide total cost approach, supply chain
competitiveness, compatibility of corporate
philosophies.
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- OPSM 639 Project Management (3
Credits)
- Managerial skills and competencies for project
management, defining a project, setting goals, defining
the scope, planning the activities, managing the
resources, organizing for project management,
implementing the project, monitoring and controlling,
and closing out the project.
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- OPSM 650 Selected Topics in
Operations Management (3 Credits)
- Topics will be announced when offered.
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- MGIS 501 Introduction to Management
Information Systems (3 Credits)
- The technological and institutional factors that
influence the choice of hardware and software components
of a management information system; introduction to
systems analysis through teamwork on an actual business
analysis problem.
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- MGIS 641 Database Management
Systems (3 Credits)
- Database concepts for management, planning, and
conceptual design, design and administration, classical
systems, relational and distributed systems,
implementation of database management systems.
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- MGIS 650 Selected Topics in
Management Information Systems (3 Credits)
- Topics will be announced when offered.
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