Logistics efficiency impacts the profitability of manufacturing companies to a large extent. According to IDC Manufacturing Insights Report of 2014, logistics cost makes up 7.87% of sales of the business. Statistics reveal that the carrying cost in China has been increased to over 3.5 trillion RMB in 2016 accounting for 5.8% of the GDP, i.e. 3% higher than the US. In our case study, the spinning mill business in China has experienced over 10% increase in warehouse and transportation costs in 2017. This study shows that by adjusting the replenishment policy and the transportation planning of cottons and yarns according to their seasonality characteristics of supply and demand, 23% of total logistics cost can be saved for the sponsor company. A multi- period Mixed Integer Linear Programming (MILP) model integrating both inventory management and transportation network of a cross region spinning mill infrastructure is developed for logistics cost minimization. Industrial-wise constraints including the cotton import quota, cotton mixing strategies and seasonality of cotton supplies can be adapted to other spinning mill companies for optimization purpose.