SAMS Subject Classification: 10, 23, 25

Climate change has become one of the, if not the most, pre-eminent environmental issues threatening the human population and natural ecosystems. The levels of greenhouse gases emitted, mainly due to burning fossil fuels, have drastically increased due to the successive industrial revolutions, increasing the likelihood of irreversible consequences. The greenhouse gas emissions of logistics processes and supply chain activities account for a majority of companies’ overall greenhouse gas emissions and carbon footprint. Most of these emissions are engendered by logistics activities related to transportation.

The carbon emissions from transportation logistics vary among supply chains and are a function of the fuel consumption of the vehicles used for transportation and distribution. Influential factors and trends contributing to fuel consumption — e.g. transport mode, vehicle attributes, driver behaviour, environmental factors, and operations — must be taken into account when attempting to minimise the environmental impact of transportation activities. There is, however, a trade-off in respect of minimising cost.

In this thesis, the aim is to investigate the utility of applying agent-based modelling and mathematical-based programming to model real-world transportation conditions and decisions related to the South African fruit export supply chain. An agent-based modelling approach is necessary so as to model the complexities associated with the various vehicle characteristics, environmental factors, traffic conditions, driver behaviour, and operational decisions. Different bi-objective mixed integer programming models are to be formulated so as to improve various aspects pertaining to the aforementioned, e.g. facility location and fleet scheduling. A decision support system (DSS) is to be designed, developed, and implemented to facilitate the decision-making process in order to aid stakeholders towards minimising both cost and carbon emissions.