Course Title: Optimisation for Decision Making

Part A: Course Overview

Course Title: Optimisation for Decision Making

Credit Points: 12.00

Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

MATH1293

City Campus

Postgraduate

145H Mathematical & Geospatial Sciences

Face-to-Face

 Sem 1 2006,
Sem 1 2007,
Sem 1 2008,
Sem 1 2009,
Sem 1 2010,
Sem 1 2011,
Sem 1 2012,
Sem 1 2013,
Sem 2 2014,
Sem 2 2015,
Sem 2 2016

MATH1293

City Campus

Postgraduate

171H School of Science

Face-to-Face

 Sem 2 2017,
Sem 2 2018,
Sem 2 2019,
Sem 2 2020,
Sem 2 2021,
Sem 2 2022,
Sem 2 2023

MATH2055

City Campus

Undergraduate

171H School of Science

Face-to-Face

 Sem 2 2022

Course Coordinator: Assoc. Prof. Melih Ozlen

Course Coordinator Phone: +61 3 9925 3007

Course Coordinator Email: melih.ozlen@rmit.edu.au

Course Coordinator Availability: By appointment


Pre-requisite Courses and Assumed Knowledge and Capabilities

Assumed Knowledge

Basic Microsoft Excel knowledge


Course Description

This course introduces approaches to solving optimisation problems faced by decision makers in today’s fast-paced business environment through building computer models to analyse and evaluate decision alternatives. By applying the methods and tools of science to management and decision making, sensible courses of action may be devised for real world problems. Extensive use will be made of appropriate software for problem solving, principally with spreadsheets.


Objectives/Learning Outcomes/Capability Development

Program Learning Outcomes 

This course is an option course so it is not required to contribute to the development of program learning outcomes (PLOs) though it may assist your achievement of several PLOs. 

For more information on the program learning outcomes for your program, please see the program guide.  


Upon successful completion of this course, you will be able to:

  1. Formulate linear, discrete and nonlinear optimisation models mathematically;  
  2. Solve optimisation problems using spreadsheets to identify the optimal solution;
  3. Utilise multiple objectives to find optimal solutions considering them; 
  4. Analyse decision-making problems where there is uncertainty using decision analysis techniques;
  5. Design Monte Carlo simulation models to make decisions 


Overview of Learning Activities

Pre-recorded lectures will explain concepts and provide guidance on independent learning and embedded tutorials within the lectures will help you master modelling and use of the software package. You will complete regular practical assessment tasks to get feedback on your progress and to practice the usage of the software package.

You are encouraged to be proactive and self-directed in your learning, asking questions of your lecturer and/or peers and seeking out information as required, especially from the numerous sources available through the RMIT library, and through links and material specific to this course that is available through myRMIT Studies Course


Overview of Learning Resources

RMIT will provide you with resources and tools for learning in this course through myRMIT Studies Course. 

There are services available to support your learning through the University Library. The Library provides guides on academic referencing and subject specialist help as well as a range of study support services. For further information, please visit the Library page on the RMIT University website and the myRMIT student portal.


Overview of Assessment

Assessment Tasks:

Assessment Task 1: Practical Assessments – Linear and Network Optimisation  
Weighting 25%  
This assessment supports CLOs 1 and 2 

Assessment Task 2: Practical Assessments – Discrete Optimisation and Decision Analysis  
Weighting 35%
This assessment supports CLOs 1, 2 and 4 

Assessment Task 3: Practical Assessments – Nonlinear and Multiobjective Optimisation and Simulation  
Weighting 40%  
This assessment supports CLOs 1, 2, 3 and 5 

If you have a long-term medical condition and/or disability it may be possible to negotiate to vary aspects of the learning or assessment methods. You can contact the program coordinator or Equitable Learning Services if you would like to find out more.