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The effects of greenhouse gas emissions, urban air pollution, and rising transport fuel prices, on the low-income capita in India, necessitate appropriate measures to ensure commodities are sustainably available. This paper presents a study whereby biodiesel blends produced from waste cooking oil are optimised for use in urban medium-duty commercial vehicles, accounting for factors of production capacity, economics, and approximated engine characteristics. An artificial neural network model, trained with experimental data, is used to predict performance, combustion, and emission parameters. The results for various biodiesel blends are applied to a standard driving cycle to obtain variations in key factors. A multi objective optimisation is carried out with engine operation parameters to arrive at optimised biodiesel blends varying between 25% and 81% based on different criteria such as minimising fuel cost, enhancing engine efficiency, and reducing emissions. Considerations when choosing blend concentration are discussed in light of different governmental targets. • Artificial neural network model for predicting engine performance using biodiesel. • Consideration of production, performance, economic, and emission criteria. • Optimisation of biodiesel blends for transport in India considering life cycle. • Blends between 25% and 81% achieved depending on optimisation parameters. [ABSTRACT FROM AUTHOR]