Scheduling and Optimisation

Subject MAST90050 (2010)

Note: This is an archived Handbook entry from 2010.

Credit Points: 12.50
Level: 9 (Graduate/Postgraduate)
Dates & Locations:

This subject has the following teaching availabilities in 2010:

Semester 2, Parkville - Taught on campus.
Pre-teaching Period Start not applicable
Teaching Period not applicable
Assessment Period End not applicable
Last date to Self-Enrol not applicable
Census Date not applicable
Last date to Withdraw without fail not applicable

Timetable can be viewed here. For information about these dates, click here.
Time Commitment: Contact Hours: 36 hours: 2 x one-hour lectures per week and 1 x one-hour computer laboratory class per week.
Total Time Commitment: 120 hours
Prerequisites: 620-616 Optimisation for Industry
Study Period Commencement:
Credit Points:
Corequisites: None
Recommended Background Knowledge: None
Non Allowed Subjects: None
Core Participation Requirements:

For the purposes of considering requests for Reasonable Adjustments under the Disability Standards for Education (Cwth 2005), and Students Experiencing Academic Disadvantage Policy, academic requirements for this subject are articulated in the Subject Description, Subject Objectives, Generic Skills and Assessment Requirements for this entry.

The University is dedicated to provide support to those with special requirements. Further details on the disability support scheme can be found at the Disability Liaison Unit website:


Dr Heng Soon Gan


Subject Overview: Scheduling is critical to manufacturing, mining, and logistics, and is of increasing importance in healthcare and service industries. Most automated systems, ranging from elevators to industrial robots, embed some kind of scheduling algorithms. Building on the Optimisation background provided in Optimisation for Industry, this subject teaches students how to solve more advanced problems. A particular focus will be scheduling problems, but other more general assignment problems will be discussed.

After completing this subject, students will:

  • be able to use advanced mathematical and computing techniques to model scheduling problems;
  • know how to develop effective mathematical methods of scheduling;
  • learn how to apply such methods in important real-life situations;
  • gain the ability to pursue further studies in this and related areas.
Assessment: Up to 60 pages of written assignments (60%: two assignments worth 30% each, due mid and late in semester), a 2-hour written examination (40%, in the examination period).
Prescribed Texts: TBA
Breadth Options:

This subject is not available as a breadth subject.

Fees Information: Subject EFTSL, Level, Discipline & Census Date
Generic Skills:

Upon the completion of this subject, students should develop:

  • Problem-solving skills (especially through tutorial exercises and assignments) including engaging with unfamiliar problems and identifying relevant strategies;
  • Analytical skills including the ability to construct and express logical arguments and to work in abstract or general terms to increase the clarity and efficiency of the analysis;
  • Ability to work in a team, through interactions with other students.
Related Course(s): Master of Science (Management Science)
Master of Science (Mathematics and Statistics)

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