Students
STAT379 – Operations Research II
2014 – S1 Day
General Information
Download as PDF
| Unit convenor and teaching staff |
Unit convenor and teaching staff
Other Staff
Sigurbjorg Gudlaugsdottir
Contact via sigurbjorg.gudlaugsdottir@mq.edu.au
E4A517
Wednesday 12-1
Unit Convenor
Barry Quinn
Contact via barry.quinn@mq.edu.au
E4A535
Tuesday 5-6, Thursday 2-3
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|---|---|
| Credit points |
Credit points
3
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| Prerequisites |
Prerequisites
39cp including STAT279(P)
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| Corequisites |
Corequisites
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| Co-badged status |
Co-badged status
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| Unit description |
Unit description
This unit complements STAT279 with the main emphasis again being on application of techniques to problems which arise in business and industry. Students are expected to use a computer package to find solutions to formulated problems. Topics include integer programming (modelling, branch-and-bound), goal programming, inventory models, decision analysis, game theory, and Markov Processes.
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Important Academic Dates
Information about important academic dates including deadlines for withdrawing from units are available at https://www.mq.edu.au/study/calendar-of-dates
Learning Outcomes
On successful completion of this unit, you will be able to:
- Be able to determine which inventory model to use, obtain the solution (by hand or Excel) and provide an inventory policy.
- Be able to set up a transition matrix, draw a state diagram, classify the states of a Markov Chain, calculate the state vector at future transitions, and when possible calculate the steady state probabilities.
- Be able to identify a zero sum or constant sum game, set up a payoff matrix, if a saddle point exists find the optimal strategy and if a saddle point does not exist to determine the mixed strategies either by formulating the game as a linear program or solving graphically.
- Be able to formulate linear programming problems involving integers and indicator variables using a computer package as well as interpret the output and write up a conclusion.
- Know about decision making under certainty and be able to provide an optimal strategy for different situations.
Assessment Tasks
| Name | Weighting | Due |
|---|---|---|
| Tutorial Participation | 5% | Weekly |
| Assignment 1 | 5% | 5pm 20 March |
| Assignment 2 | 10% | 5 pm 8 May |
| Assignment 3 | 10% | 5 pm 5 June |
| Class Test | 20% | 1 May, during tutorial |
| Final Examination | 50% | TBA |
Tutorial Participation
Due: Weekly
Weighting: 5%
To obtain full marks you need to participate in every tutorial and hand in one handwritten page from your homework solutions.
On successful completion you will be able to:
- Be able to determine which inventory model to use, obtain the solution (by hand or Excel) and provide an inventory policy.
- Be able to set up a transition matrix, draw a state diagram, classify the states of a Markov Chain, calculate the state vector at future transitions, and when possible calculate the steady state probabilities.
- Be able to identify a zero sum or constant sum game, set up a payoff matrix, if a saddle point exists find the optimal strategy and if a saddle point does not exist to determine the mixed strategies either by formulating the game as a linear program or solving graphically.
- Be able to formulate linear programming problems involving integers and indicator variables using a computer package as well as interpret the output and write up a conclusion.
- Know about decision making under certainty and be able to provide an optimal strategy for different situations.
Assignment 1
Due: 5pm 20 March
Weighting: 5%
Assignments must be submitted in pdf format online via iLearn by 2 pm on the due date. This can be done in Word or using freeware such as Cute PDF Writer. There is no "group work" assessment in this unit. All work is to be the student's own. No extensions will be granted. Students who have not submitted the assignment prior to the deadline will be awarded a mark of 0 for the assignment, except for cases in which an application for special consideration is made and approved.
On successful completion you will be able to:
- Be able to determine which inventory model to use, obtain the solution (by hand or Excel) and provide an inventory policy.
Assignment 2
Due: 5 pm 8 May
Weighting: 10%
Assignments must be submitted in pdf format online via iLearn by 2 pm on the due date. This can be done in Word or using freeware such as Cute PDF Writer. There is no "group work" assessment in this unit. All work is to be the student's own. No extensions will be granted. Students who have not submitted the assignment prior to the deadline will be awarded a mark of 0 for the assignment, except for cases in which an application for special consideration is made and approved.
On successful completion you will be able to:
- Be able to identify a zero sum or constant sum game, set up a payoff matrix, if a saddle point exists find the optimal strategy and if a saddle point does not exist to determine the mixed strategies either by formulating the game as a linear program or solving graphically.
- Be able to formulate linear programming problems involving integers and indicator variables using a computer package as well as interpret the output and write up a conclusion.
Assignment 3
Due: 5 pm 5 June
Weighting: 10%
Assignments must be submitted in pdf format online via iLearn by 2 pm on the due date. This can be done in Word or using freeware such as Cute PDF Writer. There is no "group work" assessment in this unit. All work is to be the student's own. No extensions will be granted. Students who have not submitted the assignment prior to the deadline will be awarded a mark of 0 for the assignment, except for cases in which an application for special consideration is made and approved..
On successful completion you will be able to:
- Be able to formulate linear programming problems involving integers and indicator variables using a computer package as well as interpret the output and write up a conclusion.
- Know about decision making under certainty and be able to provide an optimal strategy for different situations.
Class Test
Due: 1 May, during tutorial
Weighting: 20%
This will be held during the week 7 tutorials.
Permitted materials for the class test are a calculator, lecture notes, assignments, assignment solutions, homework solutions and tutorial solutions. There is no computer access during the class test. No electronic devices are allowed (e.g. iPhones, iPads, tablets, laptops, mobile phones) apart from non-programmable calculators.
Failure to attend the test without relevent documentation to explain the absence will result in zero marks being awarded for the test. The test is compulsory and there will be NO supplementary class tests.
The procedure for submitting a Special Consideration online can be obtained by visiting ask.mq.edu.au.
The Class Test covers lecture material from Weeks 1 - 6 inclusive and will be of 45 minutes duration.
On successful completion you will be able to:
- Be able to determine which inventory model to use, obtain the solution (by hand or Excel) and provide an inventory policy.
- Be able to set up a transition matrix, draw a state diagram, classify the states of a Markov Chain, calculate the state vector at future transitions, and when possible calculate the steady state probabilities.
- Be able to identify a zero sum or constant sum game, set up a payoff matrix, if a saddle point exists find the optimal strategy and if a saddle point does not exist to determine the mixed strategies either by formulating the game as a linear program or solving graphically.
Final Examination
Due: TBA
Weighting: 50%
The final examination will be held during the end-of-year Examination period. The final Examination is 3 hours long (with an additional 10 minutes' reading time).
The final examination covers all topics in the unit. Students may take into the final examination ONE A4 page of notes handwritten (not typed) on BOTH sides. Calculators will be needed but must not be of the text/programmable type.
You are expected to present yourself for the examination at the time and place designated in the University Examination Timetable. The timetable will be available in draft form approximately eight weeks before the commencement of examinations.
The only exemptions to sitting the Examination at the designated time are because of documented illness or unavoidable disruption. In these circumstances you may wish to consider applying for Special Consideration. Information about unavoidable disruption and the special consideration process is available at
http://www.mq.edu.au/policy/docs/special_consideration/policy.html
Students need to apply for special consideration online at https://ask.mq.edu.au
If a Supplementary Examination is granted as a result of the Special Consideration process the examination will be scheduled after the conclusion of the examination period.
NOTE: Special Consideration will only be granted to students whose performance in all parts of the coursework is satisfactory.
You are advised that it is Macquarie University policy not to set early examinations for individuals or groups of students. All students are expected to ensure that they are available until the end of the teaching semester; that is, the final day of the examination period.
On successful completion you will be able to:
- Be able to determine which inventory model to use, obtain the solution (by hand or Excel) and provide an inventory policy.
- Be able to set up a transition matrix, draw a state diagram, classify the states of a Markov Chain, calculate the state vector at future transitions, and when possible calculate the steady state probabilities.
- Be able to identify a zero sum or constant sum game, set up a payoff matrix, if a saddle point exists find the optimal strategy and if a saddle point does not exist to determine the mixed strategies either by formulating the game as a linear program or solving graphically.
- Be able to formulate linear programming problems involving integers and indicator variables using a computer package as well as interpret the output and write up a conclusion.
- Know about decision making under certainty and be able to provide an optimal strategy for different situations.
Delivery and Resources
There are 3hours of lectures and 1 tutorial each week in this unit. Lectures and tutorials commence in Week 1.
Lecture material will be put up on iLearn.
Technologies used and required
Lecture material will be placed on iLearn. Microsoft Excel and Microsoft Excel Add-in Solver will be used in some of the lectures.
Students will need to use a calculator for the final examination and some of the other assessments. Students will need to use Microsoft Excel and the Microsoft Excel Add-in Solver. All assignments must be word processed and converted to pdf files for online submission in iLearn. Cute PDF Writer (freewarre) can create pdf files from any printable document. Alternatively you can save the Word document as a PDF.
What has changed?
The random quizzes have been dropped from the assessment of this unit.
There are some minor changes in the lecture material.
Unit Schedule
| Week | Topic |
| 1 (starting 3 March) | Inventory Models |
| 2 (10 March) | Inventory Models |
| 3 (17 March) |
Inventory Models |
| 4 (24 March) | Markov Processes |
| 5 (31 March) | Markov Processes |
| 6 (7 April) | Game Theory |
| 7 (28 April) | Game Theory |
| 8 (5 May) | Integer Programming |
| 9 (12 May) | Integer Programming |
| 10 (19 May) | Integer Programming |
| 11 (26 May) | Decision Making |
| 12 (2 June) | Decision Making |
| 13 (9 June) |
Decision Making Revision |
Learning and Teaching Activities
Lecture
Tutorial
Policies and Procedures
Macquarie University policies and procedures are accessible from Policy Central. Students should be aware of the following policies in particular with regard to Learning and Teaching:
Academic Honesty Policy http://mq.edu.au/policy/docs/academic_honesty/policy.html
Assessment Policy http://mq.edu.au/policy/docs/assessment/policy.html
Grading Policy http://mq.edu.au/policy/docs/grading/policy.html
Grade Appeal Policy http://mq.edu.au/policy/docs/gradeappeal/policy.html
Grievance Management Policy http://mq.edu.au/policy/docs/grievance_management/policy.html
Disruption to Studies Policy http://www.mq.edu.au/policy/docs/disruption_studies/policy.html The Disruption to Studies Policy is effective from March 3 2014 and replaces the Special Consideration Policy.
In addition, a number of other policies can be found in the Learning and Teaching Category of Policy Central.
Student Code of Conduct
Macquarie University students have a responsibility to be familiar with the Student Code of Conduct: https://students.mq.edu.au/support/student_conduct/
Grading Policy http://www.mq.edu.au/policy/docs/grading/policy.html
Student Support
Macquarie University provides a range of support services for students. For details, visit http://students.mq.edu.au/support/
Learning Skills
Learning Skills (mq.edu.au/learningskills) provides academic writing resources and study strategies to improve your marks and take control of your study.
Student Services and Support
Students with a disability are encouraged to contact the Disability Service who can provide appropriate help with any issues that arise during their studies.
Student Enquiries
For all student enquiries, visit Student Connect at ask.mq.edu.au
IT Help
For help with University computer systems and technology, visit http://informatics.mq.edu.au/help/.
When using the University's IT, you must adhere to the Acceptable Use Policy. The policy applies to all who connect to the MQ network including students.
Graduate Capabilities
Discipline Specific Knowledge and Skills
Our graduates will take with them the intellectual development, depth and breadth of knowledge, scholarly understanding, and specific subject content in their chosen fields to make them competent and confident in their subject or profession. They will be able to demonstrate, where relevant, professional technical competence and meet professional standards. They will be able to articulate the structure of knowledge of their discipline, be able to adapt discipline-specific knowledge to novel situations, and be able to contribute from their discipline to inter-disciplinary solutions to problems.
This graduate capability is supported by:
Learning outcomes
- Be able to determine which inventory model to use, obtain the solution (by hand or Excel) and provide an inventory policy.
- Be able to set up a transition matrix, draw a state diagram, classify the states of a Markov Chain, calculate the state vector at future transitions, and when possible calculate the steady state probabilities.
- Be able to identify a zero sum or constant sum game, set up a payoff matrix, if a saddle point exists find the optimal strategy and if a saddle point does not exist to determine the mixed strategies either by formulating the game as a linear program or solving graphically.
- Be able to formulate linear programming problems involving integers and indicator variables using a computer package as well as interpret the output and write up a conclusion.
- Know about decision making under certainty and be able to provide an optimal strategy for different situations.
Assessment tasks
- Tutorial Participation
- Assignment 1
- Assignment 2
- Assignment 3
- Class Test
- Final Examination
Learning and teaching activities
- Three hours per week
- One hour per week
Critical, Analytical and Integrative Thinking
We want our graduates to be capable of reasoning, questioning and analysing, and to integrate and synthesise learning and knowledge from a range of sources and environments; to be able to critique constraints, assumptions and limitations; to be able to think independently and systemically in relation to scholarly activity, in the workplace, and in the world. We want them to have a level of scientific and information technology literacy.
This graduate capability is supported by:
Learning outcomes
- Be able to determine which inventory model to use, obtain the solution (by hand or Excel) and provide an inventory policy.
- Be able to set up a transition matrix, draw a state diagram, classify the states of a Markov Chain, calculate the state vector at future transitions, and when possible calculate the steady state probabilities.
- Be able to identify a zero sum or constant sum game, set up a payoff matrix, if a saddle point exists find the optimal strategy and if a saddle point does not exist to determine the mixed strategies either by formulating the game as a linear program or solving graphically.
- Be able to formulate linear programming problems involving integers and indicator variables using a computer package as well as interpret the output and write up a conclusion.
- Know about decision making under certainty and be able to provide an optimal strategy for different situations.
Assessment tasks
- Tutorial Participation
- Assignment 1
- Assignment 2
- Assignment 3
- Class Test
- Final Examination
Learning and teaching activities
- Three hours per week
- One hour per week
Problem Solving and Research Capability
Our graduates should be capable of researching; of analysing, and interpreting and assessing data and information in various forms; of drawing connections across fields of knowledge; and they should be able to relate their knowledge to complex situations at work or in the world, in order to diagnose and solve problems. We want them to have the confidence to take the initiative in doing so, within an awareness of their own limitations.
This graduate capability is supported by:
Learning outcomes
- Be able to determine which inventory model to use, obtain the solution (by hand or Excel) and provide an inventory policy.
- Be able to set up a transition matrix, draw a state diagram, classify the states of a Markov Chain, calculate the state vector at future transitions, and when possible calculate the steady state probabilities.
- Be able to identify a zero sum or constant sum game, set up a payoff matrix, if a saddle point exists find the optimal strategy and if a saddle point does not exist to determine the mixed strategies either by formulating the game as a linear program or solving graphically.
- Be able to formulate linear programming problems involving integers and indicator variables using a computer package as well as interpret the output and write up a conclusion.
- Know about decision making under certainty and be able to provide an optimal strategy for different situations.
Assessment tasks
- Tutorial Participation
- Assignment 1
- Assignment 2
- Assignment 3
- Class Test
- Final Examination
Learning and teaching activities
- Three hours per week
- One hour per week
Effective Communication
We want to develop in our students the ability to communicate and convey their views in forms effective with different audiences. We want our graduates to take with them the capability to read, listen, question, gather and evaluate information resources in a variety of formats, assess, write clearly, speak effectively, and to use visual communication and communication technologies as appropriate.
This graduate capability is supported by:
Learning outcomes
- Be able to determine which inventory model to use, obtain the solution (by hand or Excel) and provide an inventory policy.
- Be able to set up a transition matrix, draw a state diagram, classify the states of a Markov Chain, calculate the state vector at future transitions, and when possible calculate the steady state probabilities.
- Be able to identify a zero sum or constant sum game, set up a payoff matrix, if a saddle point exists find the optimal strategy and if a saddle point does not exist to determine the mixed strategies either by formulating the game as a linear program or solving graphically.
- Be able to formulate linear programming problems involving integers and indicator variables using a computer package as well as interpret the output and write up a conclusion.
- Know about decision making under certainty and be able to provide an optimal strategy for different situations.
Assessment tasks
- Tutorial Participation
- Assignment 1
- Assignment 2
- Assignment 3
- Class Test
- Final Examination
Learning and teaching activities
- Three hours per week
- One hour per week