Logistics cost form a major chunk of product cost for auto parts manufacturing company procuring from vendors in international market. Lot sizes and ordering frequency decisions should be made such that the total logistics cost is reduced. In order to reach to an optimal solution, it is important to identify the relevant costs before building a mathematical model for cost optimization. This case study is aimed at identifying means of cost optimization in supply chain of an automotive firm procuring form vendors in Korea, South Africa & Germany. We define a simple approach of developing linear regression models for transportation and warehousing costs. The role of LPP models in obtaining optimum solutions out of the many available solutions and cost savings is shown through a live case of Mahle Behr India Ltd. supply chain. Similar approach can be applied to other industries where transportation and warehousing costs form a big portion of the supply chain costs.