Courses

[2018 -2019 Spring : Simulation (POSTECH IMEN 481)]
Objective: To provide basic concepts of system modeling and simulation, characteristics of the discrete systems, simulation techniques, statistical methods to analyze the results, and application to real-life problems.

Course outline:

1. Fundamental simulation concepts
2. Simulation language
3. Verification & validation
4. Data collection and selecting input probability distribution
5. Random number generation
6. Output data analysis
7. Variance reduction techniques

[2017 Fall : Dynamic Programming (POSTECH IMEN 764)]
Objective: To provide the student with the art of formulating recursive equations and the method that can solve many of optimization problems involving sequential decision making.

Course outline:

1. Introduction (Sequential Decision Process, Principle of Optimality)
2. Deterministic DP : DP Algorithm
3. Deterministic DP : Shortest Path Problem and Other Applications
4. Deterministic DP : DP and Hamilton-Jacobi-Bellman (HJB) Eq.
5. Stochastic DP : Introduction to Markov Decision Process (MDP)
6. Stochastic DP : Short Review on Discrete Time Markov Chain (DTMC)
7. Stochastic DP : MDP Applications
8. Stochastic DP : Finite-Horizon MDP
9. Stochastic DP : Infinite-Horizon MDP
10. Stochastic DP : Discounted MDP and Policy/Value Iterations
11. Approximate Dynamic Programming (Reinforcement Learning)

[2016 Fall /2018 Fall : Game Theory and Business Applications (POSTECH IMEN 811)]

Objective: To provide the student with a broader strategic perspective about operations. In particular there is a focus on the following issues:
– Understanding game theory models and related concepts
– Analyze game theory models: Computing equilibria
– Understanding the classifications of interactions among stakeholders
– Using above models and concepts into some applications in various disciplines

Course outline:

1. Introduction of Game Theory
2. Static game of complete information : Cournot competition, Betrand competition, etc.
3. Dynamic game of complete information : Stakelberg game, Repeated game, Imperfect information, etc.
4. Static game of incomplete information : Bayesian game, Asymmetric information game, Auction, etc.
5. Dynamic game of incomplete information : Signaling game, Principal-Agent problem etc.
6. Applications in sypply chain coordination

[2016-2019 Spring : Probability & Statistics for Engineers (POSTECH IMEN 272)]

Objective: This course introduces students to standard methods of describing and analyzing data, probability theory, statistical inference, and ordinary least squares. The understanding of fundamental concepts and rules of probability and statistics is applied to engineering problems

Course outline:

1. Chapter 1: Introduction
2. Chapter 2: Probability
3. Chapter 3: Random Variables and Probability Distributions
4. Chapter 4: Mathematical Expectation
5. Chapter 5: Some Discrete Probability Distributions
6. Chapter 6: Some Continuous Probability Distributions
7. Chapter 7: Functions of Random Variables
8. Chapter 8: Fundamental Sampling Distributions and Data Descriptions
9. Chapter 9: One- and Two-Sample Estimation Problems
10. Chapter 10: One- and Two-Sample Tests of Hypotheses
11. Chapter 11: Simple Linear Regression and Correlation

[2012 Summer : Supply Chain Economics (Gatech ISyE 4301)]

Objective: To provide the student with a broader strategic perspective about operations. In particular there is a focus on the following issues:
– Demonstrating that many of the operational parameters (such as demand) depend on our  decisions and how to incorporate these factors into our analysis
– Developing models that incorporate strategic competitor/consumer behavior
– Understanding how market structure affects decisions
– Demonstrating the benefits of coordination and collaboration in the supply chain along with techniques for achieving and maintaining it
– Developing mathematical models for pricing, revenue management and auctions and understand how these strategies can improve profitability Applications include pricing strategies, revenue management, differentiation strategies, and incentives
Course outline:
1. Introduction
2. Review of Economic Principles: review topics include demand, price elasticity of demand, revenue, cost (marginal, average, total), profit maximization, complements and substitutes
3. Pricing Models and Strategies: components of price optimization, bundling, market segmentation strategies, and price discrimination strategies
4. Revenue Management: Pricing Models and Strategies: components of price optimization, bundling, market segmentation strategies, and price discrimination strategies
5. Games, Strategy and Equilibria: strategic interaction between firms with particular emphasis on Bertrand, Cournot, and Stackelberg games; Nash equilibrium; Pareto efficiency
6. Supply Chain Coordination: introduction to coordination strategies such as revenue sharing and transfer payments
7. Value of Information: importance of information asymmetries and agency issues; introduction to moral hazard, adverse selection and developing principal agent models
8. Business Auction: basic design of auctions and bidding strategies