Research has shown that achieving net zero emission logistics requires radical changes in both technology and logistics operations. Implementing potential solutions in the real world is risky due to the complexity and emergent nature of logistics operations. To de-risk net zero strategies we need to create a large scale, high fidelity, model so that the impact of technology, logistics strategies and policy can be assessed.
Using Agent based models and novel computational experiments SRF can identify robust low cost technological/operational mixes. This allows organisations to develop strategy, governments to draft appropriate policy, and the impact of technology to be evaluated.
Standard library of agents and objects for logistics agent based models, standard data map for logistics and robust design of experiments.
The creation of a large scale high fidelity digital twin allows researchers to design robust experiments to inform the deployment of technology, the design of policy, and the development of organisational strategy.
Researchers: Julian Allen