(Assignment due on 16/12/22, at 4pm GMT)
In this assignment, you will practice your new mathematical model building and network analysis skills in a conceptual transport infrastructure analytics problem. This assignment provides a set of tasks for the manipulation of data and strategic planning of a freight distribution system.
As part of the assignment you will be developing a set of python codes to analyse the dataset, and will be expected to submit a technical report that presents your findings.
The assignment is designed to be tackled by a group of 4-5 students. Even though the various tasks are largely interdependent, they have been selected in a way that would allow your teams to commence work in them in parallel.
Marking
Marks will be allocated to each student in accordance to the following distribution:
- 80%: for Parts 1, 2 and 3 in the group report
- 20%: for each individual submission, relating to Part 4.
The assignment is due on the 16th of December.
Submission Instructions
As a group, you will need to submit three items via Blackboard:
- Plagiarism declaration
- Report submission via TurnitIn (a single submission by one member of the group)
- Code submission in a zip file (a single submission by one member of the group)
Individually, you will also need to submit one more item:
- Short individual report for Part 4, submitted through TurnitIn
Supplementary Video (Optional)
It is completely optional to use GitHub as part of the collaborative version control process. In the following video Dr Jose Escribano Macias runs through the basics of GitHub and how to use it. You will need to create an account on GitHub using your Imperial email address and download GitHub Desktop.
View in Panopto
Hints and tips
- The list of tasks has been structured in a way that can be divided among group members. While we expect every member of the group to contribute equally to this assignment, in practice it is possible that some group members will focus more on coding, and others on preparing the discussion for the report.
- Sample Jupyter/Python notebooks have been provided that contain the majority of code that you would need to undertake these tasks, with only minor adjustments (ie. chaining of activities, or minor changes to the formulations).
- Coursework 2 can be carried out using material and theoretic concepts covered by Lectures 1 to 6.
Good luck!