Jonathan Eckstein's Business Decision Analytics under Uncertainty Classes
33:136:400:01/02
(Fall 2016)
This site is for both Fall 2016 sections of the course. The Fall
2015 version is also available.
Announcements (As of
March 21, 2017 11:46 AM)

The final exam is scheduled as follows (in the regular classroom):
 8am December 21 for the 1:40pm section (section 02)
 12pm December 23 for the 3:20pm section (section 01)

Regular office hours are now over for the semester. Special preexam
office hours will be held at the following times, and you can also email me
for an appointment:
 Tuesday, December 20, 12:304:00pm
 Thursday, December 22, 1:004:00pm (please do not use these if you
already took the exam)
Usual Office Hour Schedule
My office is 100 Rockafeller Road, room 5145. Office hours are
tentatively scheduled for
 Tuesdays 2:005:00pm from September 20 through December 13, except
 No office hours October 11 (after first midterm)
 No office hours November 15 (after second midterm)
 See the syllabus for extra office hours scheduled before exams.
This schedule is subject to change. You may also make appointments if regularly scheduled
office hours conflict with your class schedule.
Handouts and Class Materials
 Wednesday, September 7: Introduction, procedures, syllabus,
introduction to decision making under uncertainty
 Monday, September 12: Decision trees, EVSI, EVPI, start formal
probability theory
 "Colaco marketing", pages 5859 of the textbook
 Wednesday, September 14: Conditional probability, Bayes' rule
calculations, more decision trees
 Monday, September 19: More Bayes analysis and decision trees,
nonEMV decision making
 Wednesday, September 21: Some more on nonEMV decision making, start
critical fractile analysis
 Monday, September 26: More critical fractile
 Wednesday, September 28: Critical fractile case and (time
permitting) Bayesian spam filtering
 Monday, October 3: Review session for midterm
 Wednesday, October 5: Introduction to deterministic dynamic
programming
 Shortest path example on page 220223 of the book
 General "characteristics of dynamic programming" discussion
on pages 224225 of the book
 "Computational efficiency" discussion on pages 223224
 Knapsack problem example (on whiteboard, partially covered, will
finish this later)
 First
midterm exam  attend your scheduled section
 Wednesday, October 12: More deterministic dynamic programming
 Monday, October 17:
Go over exam results, basics of Python
 Wednesday, October
19: More Python, start dynamic programming in Python
 Monday, October 24: Dynamic programming in
Python
 Inventory problem Python code (slightly modified
to use "import numpy" instead of "import * from numpy")
 Integer knapsack problem Python code
 Wednesday, October 26: Start stochastic dynamic programming
 For you reference: templates for deterministic
dynamic programming
 Stochastic dynamic programming: stochastic
inventory problem on pages 276279 of the textbook
 Homework assignment
6, due November 2 (with corrected due date)

Monday, October 31: Dynamic programming with
net present value, elementary stochastic processes
 Stochastic dynamic programming for inventory
with net present value (see p. 248 of the textbook for another treatment
of this basic idea)

Binomial and Poisson distributions
 Wednesday, November 2: Using Poisson and binomial distributions in
dynamic programming
 Monday November 7: The curse of
dimensionality, begin Monte Carlo simulation
 Wednesday, November 9: Review for midterm
 Monday,
November 14: Second midterm
exam  attend your scheduled section
 Wednesday, November
16: More Monte Carlo simulation
 Monday, November 21: Go over second midterm results, start Monte
Carlo simulation of queueing models
 Monday, November 28: More simulation of queuing models
 Wednesday, November 30: Elementary queuing theory
 Monday, December 5: A bit more PollaczekKhinchin, introduction to
simulation in Arena
 Link to Arena installation file
 sorry, Arena is for Windows only!
 Link
to a newer version on the Arena website (the differences seem
fairly minimal; you must give a small amount of personal information
to complete the download)
 After downloading the installation file, unzip it
 Then, find and run setup.exe
 Enter "STUDENT" as your license number
 Various simulation model files for simple M/G/1 query server problem
 Wednesday, December 7: More discreteevent simulation with Arena
 Monday, December 12: Miscellaneous
 Wednesday, December 14: Review for final exam
Homework Solutions
All solutions will be posted on Sakai and require a
password. They are in PDF format unless otherwise specified.
 Homework
1 solution
 Homework
2 solution
 Homework
3 solution
 Homework
4 solution (handwritten and scanned  sorry, these calculations are
tedious to typeset)

Homework 5 solution (again, handwritten and scanned)

Homework
6 solution

Homework
7 solution

Homework
8 solution

Homework
9 solution

Homework
10 solution