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Optimising operations is a classic problem faced in most industries worldwide. Supply chains are becoming more complex, with more variables to be considered when trying to optimise processes. Another factor that must now also be taken into account is the amount of autonomous decision makers involved in the process, and the need to maintain individual autonomy and privacy becomes more critical.
There are often conflicting commercial interests in a supply chain, even amongst partners. It may not always be possible for one partner to provide their information to another. Research being undertaken by Anu Thomas at the IITB-Monash Research Academy aims to develop models that takes into account the conflicting objectives of each part of the supply chain and the need to maintain privacy in information sharing. Traditionally, production optimisation models have been sequential in their decision making. Thomas’s research seeks to solve such large integrated problems in a decentralised manner that involves minimal information sharing and complexity.
Take for example a coal supply chain. It has various complexities, with a need to co-ordinate multiple independent mines with a common shared rail operator, and a common shared shipping terminal to ensure the coal gets to its export destination. Each individual mine needs to determine how many train loads they need, based on their production capacity and demand, without being aware of how much capacity is actually available in the rail resources. The rail operator must also determine railing schedules based on the requests it receives from competing mining companies and its own internal capacity constraints.
Thomas’s research seeks to develop models whereby production can be optimised without each individual mine needing to divulge its commercially sensitive information to other mining companies, and to the end producer.
This research seeks to decompose what is essentially an integrated problem, and solve it in a decentralised way. This is done by formulating an integrated multi-resource constrained scheduling and production model, and then solving the problem through a decentralised iterative algorithm, based on a technique called Lagrangian relaxation and another called column generation.
The research being undertaken by Anu Thomas is under the guidance of Professor Jayendran Venkateswaran (from the Indian Institute of Technology Bombay, India), Professor Mohan Krishnamoorthy (from Monash University, Australia and CEO, IITB-Monash Research Academy) and Dr Guarav Singh (from CSIRO, the Commonwealth Scientific and Industrial Research Organisation, Australia). IITB-Monash Research Academy is a Joint Venture between the IITB and Monash. Opened in 2008, the IITB-Monash Research Academy is a graduate research school located in Mumbai that aims at enhancing research collaborations between Australia and India. Students study for a dually-badged PhD from both institutions, and spend time during their research in both India and Australia.
Thomas reflects on the importance of his research “The interactions between semi and fully autonomous decision makers are complex. My work will lead to better performance for some of these decision makers and their problems, providing practical solutions for real industrial problems, particularly as scheduling problems are now ubiquitous in our day to day life.”
This research has practical application that is far-reaching across production and supply chains, from mining to flight scheduling, industries world-wide seek to benefit from the findings.
Research Scholar: Anu Thomas, IITB-Monash Research Academy
Project Title: Integrated approaches to normally-sequential enterprise-wide optimisation problems
Supervisors: Professor Jayendran Venkateswarn, Professor Mohan Krishnamoorthy, Dr Gaurav Singh
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The above story was written by Ms Rakhee Ghelani based on inputs from the research student and IITB-Monash Research Academy. Copyright IITB-Monash Research Academy.