Department of Mathematics and Statistics/Faculty of Science
Melbourne Operations Research

Through the power of science MORe delivers greater productivity, efficiency and profitability to organisations.

Operations Research is the science of using advanced analytical methods to improving decision making.

Melbourne Operations Research (MORe) is a leading Operations Research consulting practice, based in the Department of Mathematics and Statistics at the University of Melbourne. MORe specialises in planning, scheduling and logistics.

MORe is committed to developing high quality solutions that deliver real results. For your organisation this means better informed decision making, improved efficiency and greater profitability.

Discover MORe

 

Latest News

16 March 2010 : CarLO in The Australian

MORe's CarLO is featured in The Australian. Read the article here.

25 November 2009: ASOR Recent Advances Mini-Conference 2009

Dr Heng-Soon Gan recently presented at the ASOR Recent Advances Mini-Conference held at the RMIT University...[more]

24 November 2009: MORe signs agreement with CARBONcontrol

MORe signs agreement with CARBONcontrol to deliver a complete solution to address Australian organisation's ETS challenges...[more]

3 August 2009: OR Students Work Towards an Australia Without Hunger

Operations Research students from the University of Melbourne are applying their skills to support VicRelief Foodbank. In the 3rd year Operations Research course 620-362, students work in teams to develop decision support solutions for an industry client. This year the students are delighted to be assisting VicRelief Foodbank in its quest for an Australia without hunger...[more]

16 June 2009: Try Us Out Online

Do you have complex decisions that you wish to address but are not sure how? Would you like to discover the potential for MORe to add value to your business?

At MORe we are keen to explore your ideas and investigate how we may assist in the challenges facing your organisation. Just fill in our new online form here and we will look over your situation and see how we may assist.

12 June 2009: Conference on Transportation Scheduling and Disruption Handling

The Conference on Transportation Scheduling and Disruption Handling will focus on software algorithms for optimisation of transportation schedules, focusing on the interaction between scheduling and on-the-day operation. Dr Heng-Soon Gan will chair a session presenting approaches to transportation scheduling and disruption handling based on repair techniques and local search...[more]

BREAKING NEWS!! CarLO: Addressing the ETS Challenge

Australian businesses face significant new challenges with the introduction of the Emmissions Trading Scheme (ETS). Organisations must account for their emissions liability in all areas of decision making. The emissions liability introduces a complex series of interactions between activities across the business. The proposed ETS raises additional complexities within the investment planning environment. Organisations must formulate a strategy for reducing and offsetting their carbon liability that accounts for these complexities and interactions.

To address these new challenges, a tool is required that formulates an investment strategy that incorporates both carbon and non-carbon related investments across all areas of business. Furthemore, it has to account for the complex interactions between investment activites, the emissions liability, and the requirements of the ETS. Melbourne Operations Research (MORe) has developed such a tool, Carbon Liability Optimiser (CarLO), to assist Australian businesses meet the ETS challenge.

Read more about CarLO here.

Read more about CarLO in The Australian here.

Conceptualising Optimisation

What exactly is modeling and optimisation? - Try out our new interactive modeling example and find out!

The new 'Conceptualising Optimisation' page shows how optimisation can be applied to industry problems. A simple production planning situation is presented. Users can experiment with different solutions and compare these to the optimised results. The underlying mathematical can then be examined.