FIT2033 Computer models for business decisions - Semester 2, 2015

This unit examines the principles and applications of business modelling, how a business system is used as a key component of the broad decision support system or DSS. At the completion of the subject the student should understand some of the most commonly used computer modelling techniques used in business and industry and be familiar with the applications of these techniques to the solution of business related problems. Topics will include the fundamental breakeven analysis, various types of linear programming, network models, various aspects of decision making, waiting lines systems, Monte Carlo simulation and forecasting techniques.

Mode of Delivery

South Africa (Day)

Workload Requirements

Minimum total expected workload equals 12 hours per week comprising:

(a.) Contact hours for on-campus students:

• Two hours of lectures
• One 2-hour laboratory

(b.) Study schedule for off-campus students:

• Off-campus students generally do not attend lecture and tutorial sessions, however should plan to spend equivalent time working through the relevant resources and participating in discussion groups each week.

(c.) Additional requirements (all students):

• A minimum of 8 hours independent study per week for completing lab and project work, private study and revision

See also Unit timetable information

Unit Relationships

Prohibitions

FIT2017, ETC2480, GCO2802

Prerequisites

One of FIT1006, ETW1102 or MAT1097 or equivalent

Chief Examiner

Campus Lecturer

Tutors

Your feedback to Us

Previous Student Evaluations of this Unit

Previous student feedback has shown that students find this unit to be intellectually stimulating. This semester we will be introducing some techniques from the Peer Instruction method, with the aim of improving student engagement.

Academic Overview

Learning Outcomes

On successful completion of this unit students should be able to:

• identify and apply principles of computer modelling to various business problems;
• formulate models of a range of real-world business problems, including static and probabilistic problems, and implement them using spreadsheets and other software;
• apply and analyse sensitivity analyses of computer models;
• interpret the results obtained from computer models and sensitivity analyses, and communicate these results to business and technical audiences;
• apply various decision analysis models to enhance individual, business and group decision making;
• explain, apply and be able to differentiate between various forecasting techniques with appropriate data.

Unit Schedule

Week	Activities	Assessment
0		No formal assessment or activities are undertaken in week 0
1	Introduction and Breakeven Analysis (Ref: Study Guide Part 1; Ch. 1 of Text Book)
2	Linear Programming (Ref: Study Guide Part 2; Ch. 2 of Text book)
3	Linear Programming: Computer Solution and Sensitivity Analysis (Ref: Study Guide Part 3; Ch. 3 & 4 of Text book)
4	Integer Programming (Ref: Study Guide Part 4; Ch. 5 of Text book)
5	Transportation and Assignment Problems (Ref: Study Guide Part 5; Ch. 6 of Text book)
6	Network Problems (Ref: Study Guide Part 6; Ch. 7 of Text book)	Assignment 1 due Week 6
7	Multicriteria Decision Making (Ref: Study Guide Part 7; Ch. 9 of Text book)
8	Decision Making Theory (Ref: Study Guide Part 8; Ch. 11 & 12 of Text book)
9	Decision Trees (Ref: Study Guide Part 9; Ch. 11 & 12 of Text book)
10	Queuing Analysis (Ref: Study Guide Part 10; Ch. 13 of Text book)
11	Monte Carlo Simulation (Ref: Study Guide Part 11; Ch. 14 of Text book)	Assignment 2 due Week 11
12	Forecasting (Ref: Study Guide Part 12; Ch. 15 of Text book)
	SWOT VAC	No formal assessment is undertaken in SWOT VAC
	Examination period	LINK to Assessment Policy: http://policy.monash.edu.au/policy-bank/ academic/education/assessment/ assessment-in-coursework-policy.html

*Unit Schedule details will be maintained and communicated to you via your learning system.

Teaching Approach

• Lecture and tutorials or problem classes
  This teaching and learning approach provides facilitated learning, practical exploration and peer learning.
• Peer assisted learning
  This approach aims to engage students through pre-class and in-class activities that require students to understand and explain core concepts in small groups.

Assessment Summary

Examination (3 hours): 60%; In-semester assessment: 40%

Assessment Task	Value	Due Date
Assignment 1	20%	Week 6
Assignment 2	20%	Week 11
Examination 1	60%	To be advised

Assessment Requirements

Assessment Policy

Assessment Tasks

Participation

• Assessment task 1

  Title:

  Assignment 1

  Description:

  Assessment of Study Guides 1 - 6. This assignment will consist of a number of business problems.

  Weighting:

  20%

  Criteria for assessment:

  The solution to each problem will be assessed according to the following criteria:

  • How well the business problem has been understood
  • How well the given business problem has been formulated into a mathematical model
  • The accuracy with which the mathematical model has been coded up as a spreadsheet model
  • The clarity and neatness of the presentation of the spreadsheet model
  • The degree to which the spreadsheet model implements good design techniques
  • The degree to which the model constructed is an accurate reflection of the given business problem
  • The effective and accurate use of appropriate solution techniques to solve the resultant spreadsheet model
  • The clarity and quality of presentation of the final solution, and the degree to which it solves the initial business problem

  Due date:

  Week 6

  Remarks:

  This assignment will require students to demonstrate mastery of learning outcomes 1, 2, 3 & 4.

• Assessment task 2

  Title:

  Assignment 2

  Description:

  Assessment of Study Guides 7 - 12. This assignment will consist of a number of business problems.

  Weighting:

  20%

  Criteria for assessment:

  The solution to each problem will be assessed according to the following criteria:

  • How well the business problem has been understood
  • How well the given business problem has been formulated into a mathematical model
  • The accuracy with which the mathematical model has been coded up as a spreadsheet model
  • The clarity and neatness of the presentation of the spreadsheet model
  • The degree to which the spreadsheet model implements good design techniques
  • The degree to which the model constructed is an accurate reflection of the given business problem
  • The effective and accurate use of appropriate solution techniques to solve the resultant spreadsheet model
  • The clarity and quality of presentation of the final solution, and the degree to which it solves the initial business problem

  Due date:

  Week 11

  Remarks:

  This assignment will require students to demonstrate mastery of learning outcomes 1, 2, 5 & 6.

Examinations

• Examination 1

  Weighting:

  60%

  Length:

  3 hours

  Type (open/closed book):

  Closed book

  Electronic devices allowed in the exam:

  Calculators

  Remarks:

  Students are permitted to bring a formula sheet into the exam. This may be hand written or typed, but may not be more than one (1) A4 sheet of paper with writting on both sides.

Learning resources

Feedback to you

• Informal feedback on progress in labs/tutes
• Graded assignments with comments
• Solutions to tutes, labs and assignments

Extensions and penalties

Returning assignments

Assignment submission

Online submission

All assignments for this unit must be submitted electronically through the Moodle site for this unit. This can be accessed via the links in your my.monash.edu portal. Assignment coversheets will take the form of an online quiz. You will need to complete the quiz before you can submit the assignment.

Required Resources

On-campus students, and those studying at supported study locations may use the facilities available in the computing labs. Information about computer use for students is available from the ITS Student Resource Guide in the Monash University Handbook. You will need to allocate up to 5 hours per week in some weeks for use of a computer, including time for newsgroup access and discussion groups.

Students studying off-campus are required to have the minimum system configuration specified by the Faculty as a condition of accepting admission, and regular internet access.

Prescribed text(s)

Taylor, B.W. III. (2012). Introduction to Management Science. (11th Edition) Prentice Hall (ISBN: 10: 0273766406 or 13: 978-0273766407).

Recommended Resources

The three Excel based software packages: Excel QM, Crystal Ball and TreePlan are included in the prescribed text book.

Recommended text(s)

D. R. Anderson, D. J. Sweeney and T. A. Williams. (2005). An Introduction to Management Science. () Thomson Learning.

W. L. Winston, S. C. Albright and M. Broadie. (2001). Practical Management Science. (2nd Edition) Duxbury Press.

J. A. Lawrence Jr. and B. A. Pasternack. (1998). Applied Management Science. () John Wiley & Sons Inc.

Examination material or equipment

Refer to the FIT2033 unit on Moodle for any additional details.

Other Information

Policies

Graduate Attributes Policy

Student Charter

Student services

Monash University Library

Disability Liaison Unit

Other

Study resources provided:

• A online Unit Book containing 12 Study Guides.
• This Unit Guide outlining the administrative information for the unit.
• The FIT2033 website on Moodle, where lecture slides, weekly tutorial requirements, assignment specifications and sample solutions will be posted.
• Newsgroups that can be linked to from the Unit website.
• Access to past exam papers.