Transportation Cost and Tariff Optimization in the Specialty Tire and Wheels Industry

Abstract

Complexity arises as products can take multiple transportation paths that flow from manufacturing sites through to different distribution centers and onward to the end customer destination. Changing transportation costs and volatile tariff rates exacerbate this complexity, as established product flows may become sub-optimal from a cost perspective. Optimization models can be used to determine the lowest-cost solution to ship products from the manufacturing origin to the end customer. This Capstone developed a mixed integer linear programming model for Carlstar, a global leader in the specialty tire and wheel industry. The objective was to identify the optimal routing solution to minimize transportation and tariff costs for each of the company’s five product market segments. The model provided for multiple possible routing options, including shipping direct to the customer from the manufacturer or through a distribution center. Multiple scenarios were run using different rates for transportation costs, tariffs, and customer demand. Model constraints included manufacturing location, demand, and flow balance through the distribution centers. Results indicate that Carlstar could save almost 20% on distribution costs by increasing the number of direct to customer shipments. The impacts of tariffs, demand fluctuations and handling costs were smaller than expected, indicating that once an updated transportation network is established, it would not have to be updated very often to maximize potential cost savings.