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When studying relevant research in the emerging field of green supply chain optimization, it is currently difficult to find modeling that provides a realistic, multi-nodal distribution process concerned with large-scale freight manufacturing and transport. Seen even more rarely is a combined objective that is focused on minimizing both cost and environmental impact. This thesis aims to fill that gap, as it follows products sold by a major US retailer from its manufacturing in Southern China to arrival, processing, and distribution in the United States. A multi-objective, linear optimization model is used. Decision variables include manufacturer, transportation method, port selection, distribution center selection, and timing. The paper utilizes published methodology for carbon emissions calculation and carbon market prices, and provides sensitivity analyses to extrapolate findings into real-world solutions. Many global organizations and nations have taken steps aimed at becoming carbon neutral. As the transportation sector makes up nearly one-third of all greenhouse gas emissions, it is important to explore options related to freight that reduce these emissions prior to any government regulations being enforced. The formulated linear program provides a breadth of decisions that contribute to moving products and satisfying demand. These decisions not only include location sourcing and time period selection, but also carbon-focused aspects of freight movement, including vehicle choice. The model formulated in this thesis allows interested corporations to customize inputs and evaluate the model using organization-specific parameters, enabling a holistic view of current operations from both an economic and environmentally conscious angle.