Module and Programme Catalogue

Search site

Find information on

This module is inactive in the selected year. The information shown below is for the academic year that the module was last running in, prior to the year selected.

2019/20 Taught Postgraduate Module Catalogue

COMP5920M Scheduling

15 creditsClass Size: 40

Module manager: Dr Raymond Kwan
Email: R.S.Kwan@leeds.ac.uk

Taught: Semester 2 (Jan to Jun) View Timetable

Year running 2019/20

This module is not approved as an Elective

Objectives

On completion of this module, students should be able to:
- The main objectives are to explore the subject of scheduling from several perspectives, theoretical and practical, and to gain practical experience through coursework assignments.
- Appreciate scheduling optimization from a range of practical problems, e.g, in transport, computer network and health care;
- Model real life scheduling problems taking into account of problem contexts, decision variables, optimization objectives and constraints;
- Appreciate state-of-the-art approaches and solution strategies in designing practical scheduling optimization algorithms.

Learning outcomes
On completion of this module, students should be able to:
- Appreciate scheduling optimization from a range of practical problems, e.g, in transport, computer network and health care;
- Model real life scheduling problems taking into account of problem contexts, decision variables, optimization objectives and constraints;
- Appreciate state-of-the-art approaches and solution strategies in designing practical scheduling optimization algorithms.

Skills outcomes
Scheduling approaches and algorithms.
Interdiscplinary problem solving


Syllabus

- Scheduling problems: train crew scheduling and rostering; bus vehicle scheduling; University course timetabling; hospital nurse scheduling.
- Scheduling contexts: regular operational planning; short-term planning; real-time; time-windowed scheduling; deterministic; stochastic.
- Scheduling approaches and algorithmic techniques: exact methods; integer linear programming; heuristics (including meta-heuristics and hyper-heuristics); evolutionary algorithms.
- Case studies: TrainTRACS (a commercial train crew scheduling package); pilot projects of train companies adopting automatic scheduling software.

Teaching methods

Delivery typeNumberLength hoursStudent hours
Lectures221.0022.00
Class tests, exams and assessment12.002.00
Private study hours126.00
Total Contact hours24.00
Total hours (100hr per 10 credits)150.00

Private study

Taught session prep: 22 hours
Taught session follow-up: 44 hours
Self-directed study: 25 hours
Assessment activities: 35 hours

Opportunities for Formative Feedback

Attendance and formative assessment.

Methods of assessment


Coursework
Assessment typeNotes% of formal assessment
ReportMini research exercise20.00
Problem SheetProblem sheet20.00
Total percentage (Assessment Coursework)40.00

This module is re-assessed by exam only.


Exams
Exam typeExam duration% of formal assessment
Standard exam (closed essays, MCQs etc)2 hr 00 mins60.00
Total percentage (Assessment Exams)60.00

This module is re-assessed by exam only.

Reading list

The reading list is available from the Library website

Last updated: 30/04/2019

Disclaimer

Browse Other Catalogues

Errors, omissions, failed links etc should be notified to the Catalogue Team.PROD

© Copyright Leeds 2019