Greenhouse Gas Optimization Across a Multi-Echelon Manufacturing and Distribution Network

Abstract

Emissions from the industrial sector are a major contributor to climate change around the world. Many of these industrial emissions are attributable to the supply chain and will need to be drastically reduced to meet emission goals set forth by the United Nations Paris Agreement. Possibilities including renewable energy technologies for manufacturing and sustainable vehicles for transportation already exist and can help to reduce emissions across the supply chain, but few solutions have been evaluated regarding re-organizing supply chains as a whole to minimize carbon footprint. This thesis focuses on adapting sourcing strategies in a multi-echelon supply chain network to minimize Greenhouse Gas emissions. An approach using a multi-objective mixed-integer linear program that balances emission reduction along with other objectives such as sourcing cost, lead time, and supply risk is conducted to test the feasibility of the developed strategy in a business context. Opportunities for improvement of the model and possibilities for implementation in other organizations are evaluated.