OR Methods
 IE 411 Mathematical Programming (BT)
Nonlinear optimization, convexity, Karush-Kuhn-Tucker conditions, line search, constrained optimization, quadratic,
programming, large scale linear programming and decomposition, polyhedral analysis.
 IE 412 Large Scale Optimization and Applications (HY)
The aim of this course is to present decomposition based methods to solve linear and integer programming problems of large
sizes that we encounter in practice. The course covers methods like Lagrangian relaxation, cutting plane, Dantzig-Wolfe
decomposition, column generation, and Benders's decomposition with applications in production planning, location, routing,
network design, workforce scheduling, and capacity allocation.
 IE 420 Heuristics in Optimization (IS)
Fundamental concepts of heuristics in solving various optimization problems with emphasis on meta-heuristics such as
simulated annealing, tabu search, genetic algorithms, and ant algorithms. The basic material on heuristics will be covered in
regular lectures. The students will be required to present a variety of application papers on different subjects related to the
course. In addition, as a project assignment, the students will design a heuristic, write a code of an appropriate algorithm for
the problem and evaluate its performance.
 IE 421 Introduction to Stochastic Processes
Random variables, conditional expectation. Bernoulli and poisson processes. Discrete time Markov chains: classification of
states, ergodic properties. Random walks, branching processes. Continuous time Markov processes. Kolmogorov differential
equations. Birth and death processes, renewal process.
 IE 422 Dynamic Programming
Deterministic and discrete-time stochastic dynamic programming; principle of optimality, forward and backward formulations,
Markov decision processes under discounted and average payoff criteria, bandit problems, stochastic games. Applications;
shortest path problems, resource allocation, stock options, inventory control, maintenance problems, knapsack and assignment
problems.
 IE 434 Stochastic Models in Operations Research (NE)
Review of conditional probability; Markov chains, example models, Markov Chains with rewards; Markov decision processes,
solution algorithms; an introduction to renewal theory and applications; queueing models, example applications in service
systems; reliability models; other topics.
 IE 443 Multi-Objective Decision Analysis (MRT)
This course is designed to cover quantitative decision analysis. The course begins with the structuring of objectives and value
hierarchies, and determination of value functions. After introducing consistent characterization of preferences under certainty,
it proceeds with value analysis under uncertainty including expected value analysis, utility theory, multi-attribute risk aversion,
certainty equivalent calculations and the analytical hierarchy process.
Production and Manufacturing
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IE 423 Forecasting Methods and Applications (UG)
Basic quantitative methods of forecasting are introduced. Time series decomposition, Regression methods, exponential smoothing and ARIMA models will be
covered. Judgemental forecasting will also be briefly mentioned. Applications in Engineering will be emphasised.
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IE 428 Project Scheduling (OO)
Introduction to project network analysis with CPM and PERT. Time-cost trade-off and learning curve analysis in relation to makespan minimization.
Mathematical programming models for resource allocation and scheduling under resource constraints. Financial aspects including cash flow management. Exact
and heuristic methods for solving the scheduling and resource management problems.
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IE 441 Cost Analysis and Control
Fundamentals of managerial cost accounting practices applied to manufacturing and service organizations. Cost terms, cost-volume-profit analysis, job costing,
activity based costing as bases of accounting systems. Master budgets and flexible budgets for planning and control. Determination of cost behaviour and pricing
decisions, cost allocation and revenues for profitability analysis.
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IE 443 Multi-Objective Decision Analysis (MRT)
This course is designed to cover quantitative decision analysis. The course begins with the structuring of objectives and value hierarchies, and determination of
value functions. After introducing consistent characterization of preferences under certainty, it proceeds with value analysis under uncertainty including expected
value analysis, utility theory, multi-attribute risk aversion, certainty equivalent calculations and the analytical hierarchy process.
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IE 462 Introduction to Advanced Manufacturing Technologies (SA)
A study of the present impact of computers and automation on manufacturing. product design technologies. Concepts and principles of computer aided design
and process planning; automated production lines; group technology; cellular manufacturing; flexible manufacturing systems; automated material handling.
Introduction to robotics technology, work cell design and applications.
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IE 463 Operations Scheduling (MRT)
This course is designed to provide an introduction to the area of scheduling. Selected problems from a variety of manufacturing and service applications
including job shop problems, assembly systems, reservation systems, timetabling problems, and workforce and crew scheduling will be presented. Exact and
approximate techniques and approaches to modeling and solving these problems will be discussed. A brief overview of the current trends and future directions
will be included.
Production and Manufacturing
 IE 464 Inventory Theory (OA)
This course focuses on various inventory control problems in service and manufacturing environments. First, deterministic
models and their extensions are introduced. Single and multi item problems, quantity discount case, effect of inflation,
classification of inventories are discussed. Second part of the course focuses on finite and infinite horizon problems with
stochastic demand. Models for periodic and continuous review policies, coordinated replenishment problems, perishable items
are examined. Finally, multi echelon inventory problems in supply chain context are introduced.
 IE 465 Modeling and Analysis of Production Systems (OA)
This course covers fundamental concepts for describing and analyzing production systems dynamics. Several performance
measures of production systems, such ascycle time, throughput, WIP, fill rate, utilization etc. are analyzed through several
quantitative tools. The influence of variability on such systems and the causes and types of variability are analyzed in details.
Analysis and comparison of push and pull production systems, including a comparison of CONWIP, Kanban, and MRP
approaches, are also covered.
 IE 467 Emerging Trends in Manufacturing (YK)
This course will introduce recent developments in the areas of micro/nano/bio manufacturing and sustainability. Design and
manufacturing process optimization techniques will also be covered with potential applications in CAD/CAM, rapid
prototyping and robotics. Students will be required to complete a group project.
 IE 474 Facility Layout and Location (BT)
This course addresses issues that arise in facilities planning. Main issues addressed include optimally choosing the locations of
single or multiple facilities and layout design. The focus is on analytical methods for solving such problems.
Supply Chain and Logistics
 IE 423 Forecasting Methods and Applications (UG)
Basic quantitative methods of forecasting are introduced. Time series decomposition, Regression methods, exponential
smoothing and ARIMA models will be covered. Judgemental forecasting will also be briefly mentioned. Applications in
Engineering will be emphasised.
 IE 460 Quantitative Models in Supply Chain Management (AT, NE, AS)
The purpose of this course is to introduce the quantitative models to analyze buyer-vendor relations across different functions
and stages of supply chain. The topics covered include quantity and transportation discounts, multi-stage inventory and
production systems, decentralized and centralized modeling approaches, strategic games in supply chains, and contracting.
 IE 461 Supply Chain Management (AT, NE, AS)
A supply chain consists of all stages involved, directly and indirectly, in fulfilling a customer request. Supply chain
management deals with the management of materials, information and financial flows in the supply chain to maximize total
profitability. The topics that are covered in this course include review of inventory management and risk pooling, logistics
network configuration, the value of information in supply chains, distribution strategies and strategic alliances, supply chain
contracts, international issues in supply chain management, coordinated product and supply chain design, information
technology for supply chain management
 IE 464 Inventory Theory (OA)
This course focuses on various inventory control problems in service and manufacturing environments. First, deterministic
models and their extensions are introduced. Single and multi item problems, quantity discount case, effect of inflation,
classification of inventories are discussed. Second part of the course focuses on finite and infinite horizon problems with
stochastic demand. Models for periodic and continuous review policies, coordinated replenishment problems, perishable items
are examined. Finally, multi echelon inventory problems in supply chain context are introduced.
Supply Chain and Logistics
 IE 468 Revenue and Pricing Optimization (AS)
Pricing and revenue optimization focuses on how a firm should set and update pricing and product availability decisions in
order to maximize its profitability. This course introduces the theory, concepts and applications of pricing and revenue
optimization. The topics include a review of price-demand functions, price differentiation, pricing under constrained supply,
revenue management, capacity allocation, multi-item revenue management, overbooking and dynamic pricing & markdown
management.
 IE 474 Facility Layout and Location (BT)
This course addresses issues that arise in facilities planning. Main issues addressed include optimally choosing the locations of
single or multiple facilities and layout design. The focus is on analytical methods for solving such problems.
 IE 479 Distribution Logistics (BYK)
This course focuses on the distribution of goods and services from their points of creation to their customers. Designing the
logistics network with main emphasis on location models will constitute the first part of the course. In the second part of the
course planning and controlling of freight-transportation will be covered. Practical aspects of the models and methodologies
covered will be emphasized through computational assignments.
 IE 482 Humanitarian Logistics (BYK)
This course will provide an introduction to some important problems with societal impact and explore how OR/MS tools can
be used in addressing those problems. Some of these problems are related to meeting the ongoing needs of the society, such as
ambulance assignment and routing, location of public service facilities (e.g., fire stations and community health centers),
delivery of meals to senior citizens, delivery of blood to hospitals, and public transportation. In addition to these ongoing
needs, OR/MS tools can also have a tremendous impact in preparing for, responding to, and recovering from disasters. The
aim of this course is to provide students with an understanding of humanitarian operations by introducing the context in which
they take place, the organizations (UN Humanitarian agencies, NGOs, public and private sector), and the activities and
challenges in the supply chain for the procurement, delivery, warehousing and distribution of the aid.
Financial Engineering
 IE 440 Introduction to Financial Engineering (SD)
Financial markets (bonds, stocks, futures, forwards, options, interest rates and their term structures), models of security prices
(Brownian motion, geometric Brownian motions, Ornstein-Uhlenbeck processes, Cox-Ross-Rubinstein binomial model,
Merton-Black-Scholes model), pricing and hedging financial derivatives (Ito’s rule, stochastic integration, diffusion processes,
probabilistic solutions of PDEs, no-arbitrage pricing in a complete market of futures, forwards, European and American type
options, pricing in incomplete markets), Hedging with futures and options, bond hedging, numerical methods (pricing using
trees, Monte-Carlo simulations, finite-difference methods), mean-variance analysis of portfolios, value at risk, optimal
consumption and portfolio strategies (formulations and solutions of appropriate dynamic programming models and HamiltonJacobi-Bellman equations).
 IE 444 Operations Research in Finance (MCP)
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This course aims to introduce industrial engineering students to mainstream optimization tools and models used in modern
finance. It will begin with a review of pertinent optimization technology, and develop from scratch basic financial
optimization models. GAMS and XPRESS-MP modeling and optimization software systems will be used in homework
assignments
 IE 446 Introduction to Continuous Time Finance (MCP)
This course aims to introduce students with no or little background on finance to the rudiments of continuous time financial
option evaluation. The treatment is at an elementary level. The topics covered are Brownian Motion, Geometric Brownian
Motion with Drift, Ito's Lemma, Black-Scholes Analysis, Hedging in Continuous Time, American options, Portfolio
Optimization in Continuous Time, Merton's Problem, and Monte Carlo Methods if time permits.