-Developed a supply chain network baseline MIP model for a glass manufacuterer with multiple products, manufacuting facilites, and production costs (Regular/Overtime) to find optimal product flow as per sourcing policies and capacity constraints. -To improve the service levels, developed a multi-objective MIP scenario model which finds the minmum number of warehouses to be built such that 80% of the demand is covered with in 500 miles of the nearest source. -Scenario model suggested to build 5 warehouses with their exact location and product flow information and was able to achieve reduction in transporatation cost by 19.75% with 80% demand served within 500 miles compared to 11% of demand within 500 miles in baseline model. -Coded in Python and performed optimization using Gurobi: pandas, dictionaries, loops, gurobi packages, csv package.