Dr Divya Jayakumar Nair

Divya Jayakumar NairIt would surprise many people to know that thousands of tons of fresh food is thrown into landfill each year by the food industry. However, the process of ‘rescuing’ this food and getting it to places and people who could benefit from it is more complex than it might seem.

Like in most the real-life decision-making processes, handling risk and uncertainties is considered critical in food rescue operations. Operations are complex and relatively little work is done on the topic, so food rescue distribution is an area with potential research opportunities. Many researchers have explored the logistical problems in the commercial sector, but the problem of food rescue and redistribution is still relatively open.

This is an area that fascinated me, so I decided to pursue my PhD in the logistics of surplus food rescue and distribution. Through my research I hope to make the industry more efficient by looking at things like traffic assignment and the logistics of supply chain systems.

The UNSW Australia, School of Civil and Environmental Engineering’s dedicated transport group, rCITI, has a worldwide reputation in the field of transportation and I am fortunate to be given the opportunity to study here among excellent, like-minded peers with the support of passionate academics.

Divya's rCITI/ OzHarvest project with Prof Vinayak Dixit, A/Prof Taha Hossein Rashidi, Dr David Rey and Dr Hanna Grzybowska was funded by an Australian Research Council Linkage grant aim was to develop a multi-objective dynamic vehicle routing algorithm that would help OzHarvest pick up and deliver the largest amount of food, to the most appropriate location, with minimal wastage, in the most timely, equitable and cost-effective manner. 

With so many variables to consider it was a complex challenge for the rCITI team. The multi-objective model aimed to combine fairness in allocation and cost-effective routing without imposing restrictions on donor and welfare agencies. The team’s final route update approach was computationally efficient and provided a lower route cost, a minimum wastage of perishable products and a reasonable fairness in allocation.

The result was an algorithm that can be used to not just support decision making at OzHarvest but is flexible enough to be adapted for use by organisations facing similar challenges anywhere in the world.