This table provides information about both the lecture (L) and recitation (R) sessions.
| SES # | TOPICS | KEY DATES |
|---|---|---|
| Introduction to course | ||
| L1 | Motivation: paradigm shift from best outcome to moving distribution of outcomes to right | ESD.70J in parallel for 4 days |
| Part 1: basics, recognition of uncertainty, valuation fundamentals, and timing issues | ||
| Conventional valuation and recognition of uncertainty | ||
| L2 |
Discounted cash flow and present value Criteria for valuation |
|
| R1 | Valuation methods and discussion for uncertainty exercise | |
| L3 | Uncertainty recognition | |
| L4 |
Choice of discount rate Opportunity cost, weighted average cost of capital, capital asset pricing model |
Application Portfolio 1 due: Topic definition |
| R2 | Discussion of choice of discount rate and production functions | |
| Timing of development | ||
| Basic issue: build now or later? | ||
| L5 |
Asphalt vs. concrete highways Basic system model: production function, economies of scale |
|
| L6 | Optimum expansion size deterministic case | |
| R3 | Exercises on production functions and economies of scale | |
| L7 |
Determining economies of scale from cost function Constrained optimization and marginal analysis |
|
| L8 |
Sources of flexibility “On” systems-timing “In” systems-timing and function Case examples |
Application Portfolio 2 due: Defining uncertainties |
| R4 |
Discussion of flexibility in application portfolio Review of probability determination from data and Bayesian analysis |
|
| Part 2: uncertainty modeling and flexibility valuation methods | ||
| Decision analysis | ||
| L9 | Uncertainty assessment | |
| L10 |
Primitive models Introduction to decision analysis |
|
| R5 | Decision analysis practice | |
| L11 |
Practical issues Solutions by “folding back” Flaw of averages |
Application Portfolio 3 due: Flexibility identification |
| L12 |
Distribution of outcomes for decision analysis Value at risk and gain, multiple value metrics |
|
| R6 | Value of information and flexibility | |
| L13 | Benefits of waiting: value of information | |
| L14 | Decision analysis examples: oil platform, wind energy, silicon wafer plant, Tokyo/Haneda runway | Application Portfolio 4 due: Decision analysis |
| R7 | Past midterm solutions | |
| L15 | Mid-semester review | |
| L16 | Midterm exam | |
| Lattice analysis | ||
| L17 |
Lattice model to represent uncertainty Regression to determine trend and variability (μ and σ) |
|
| R8 | Review of midterm and of regression analysis | |
| L18 | Dynamic programming: systematic solution by “folding back” | |
| R9 | Dynamic programming and valuation of lattice model | |
| L19 |
Valuation of lattice by dynamic programming Satellite case study |
|
| L20 |
Combining lattice and decision analysis Case studies: aqua line tunnel |
Application Portfolio 5 due: Lattice analysis of evolution of a major uncertainty |
| L21 | Conceptual valuation and application | Application Portfolio 6 due: Decision analysis using lattice |
| R10 | Advice on application portfolios | |
| L22 | Comparing decision analysis and lattice analysis | |
| L23 |
Definition and analysis of “hotspots” using change propagation analysis Path dependency Comments on draft application portfolio Case studies: car platforms, hydroelectric dam, mini unmanned aerial vehicle |
Draft of complete portfolio due |
| L24 | Perspective on flexibility in design and real options analysis (Part 1) | Complete revised portfolio due |
| L25 | Perspective on flexibility in design and real options analysis (Part 2) | |
| L26 | Review for final exam | |
