Microsoft Word - Assignment 3.docx
MATH7232 Operations Research & Mathematical Planning 2018
Assignment 3 – Dynamic Programming
This assignment is due by 6pm on Friday, May 25th and is worth 10% of your final grade. You
can do each assignment in pairs, with a single submission.
Your job with an Operations Research consulting company is going well. Your boss and
client would like you to continue working to help Pure Fresh improve their operations and
that of their customers, including the corner store Jenny’s Juices. Communications to you
from the company will be provided at
https:
courses.smp.uq.edu.au/MATH7232
The first communication is already available with the final communication appearing on
or before Friday, May 11th.
You will need to prepare a report which includes two main sections:
Section A – Report to your boss
• A general formulation that describes the data, stages, states, actions and the
transition and value functions used in your two models. 8 marks
• A single Python file with your implementations. This should be easy to relate back
to the formulation. Your boss will attempt to execute this model. 6 marks
Section B – Report to the client
• Written responses that clearly and concisely address the needs of the client given
through the communications. 6 marks
Submit your report and Python files via Blackboard, using PDF for the report (saved from
Word or created in LaTeX).
Only one submission per pair is necessary but make sure both names are clearly shown on
your report. Each student will receive separate data from the client but a pair need only
consider one data set in the report.
Grading Criteria
Section A
Marks 0 1 2
Data Missing some or all descriptions of data
Co
ectly describes all data
Stages Missing clear description of stages
Co
ectly describes stages
States Inco
ect or missing description of states
Co
ectly describes state
for one communication
Co
ectly describes states
for all communications
Actions Inco
ect or missing description of actions
Co
ectly describes actions
for one communication
Co
ectly describes actions
for all communications
Value function
Inco
ect or missing
description of value
functions
Co
ectly describes value
function for one
communication
Co
ectly describes value
functions for all
communications
Python code
There is no relationship
etween Python code and
mathematical formulation
Python code mostly
matches mathematical
formulation
Python code clearly
matches mathematical
formulation
Execution Python code fails to run Python code runs but gives inco
ect answer
Python code runs and gives
co
ect answer
Efficiency Python implementation is slow to run
Python implementation is
efficient
Utility
Difficult to determine
optimal strategy from
Python implementation
Easy to determine optimal
strategy from Python
implementation
Section B
Marks 0 1 2
Response to
communications
Fails to address any of the
client questions
Co
ectly addresses one
client question
Co
ectly addresses all
client questions
Written response
Poorly written response
with frequent e
ors in
grammar, spelling or
technical language; and/or
unnecessarily long
Concisely addresses needs
of client with few e
ors in
writing
Excellent proficiency in
clearly and concisely
addressing needs of client
Strategies
Poor or missing description
of optimal strategies for
stochastic models
Good description of optimal
strategies for stochastic
models
Clear and insightful
description of optimal
strategies for stochastic
models