Optimisation in Business and Industry
This course showcases the enormous impact of optimisation in business and industry, particularly in supply chain logistics. Optimisation forms the basis for strategic planning in many key sectors, and underpins much decision support software for operational planning and scheduling. With the growth of larger, more complex, and often global enterprises, optimisation has become an essential tool for the planning and management of such enterprises. Many businesses and industry depend critically on optimisation for their profitability.
The course will investigate mathematical approaches used in recent years to address critical issues for business and industry, particularly in the areas of logistics and supply chains. Integrated supply chain modelling, network planning, inventory management, and approaches to solutions of large-scale models will all be explored.
- Semester 2 - 2016
- Semester 2 - 2017
On successful completion of the course students will be able to:
1. An understanding of the complexities and scale of modern business operations, and the use of optimisation models to design and manage them
2. Advanced skills in modelling large, complex, business and industrial optimisation problems
3. Increased abilities to model and solve business problems with advanced operations research techniques.
The course will discuss recent cases of the application of optimisation and mathematical techniques to address business issues. It will cover the use of both strategic and operational planning models.
The course will span a range of business planning problems, but with a focus on:
- logistics and supply chains,
- integrated modelling,
- large-scale modelling,
- network planning,
- co-ordination and collaboration, and
- inventory management.
The use of appropriate software for modelling will be incorporated, and students will be asked to practice modelling business problems with this software.
Two courses from: MATH1110 or MATH1210, STAT1060 or STAT1070 MATH1510, ECON1003, EBUS2123 (BBus students are strongly advised to complete EBus2123 before enrolling in MATH3840) .
Written Assignment: Written Assignments
Project: Group Project and Presentation
Formal Examination: Examination
Case Study / Problem Based Learning: Individual Case Study
Face to Face On Campus 3 hour(s) per Week for Full Term
Tutorial/computer lab work will be integrated with lecture material.