Supply chain studies have been key areas for optimization across many sectors. However, with the changing landscape of geo-economic factors in the Middle East, coupled with increased complexities within the supply chain network and growing competitiveness amongst industries, optimization studies have naturally become more complex overtime. This thesis considers a case study for a major lubrication company in Saudi Arabia. The case study addresses a single-sourcing network redesign problem for a four-level supply chain consisting of suppliers, plants, distribution centers (DC’s) and markets. The demand, land prices, and energy prices are uncertain parameters with DC-to-market dependent lead times. The objective is to determine the optimal number and locations of plants and DC’s, the assignment of each plant-DC and DC-market, which minimizes the system-wide location, transportation, and inventory costs for each scenario. The problem is formulated as mixed integer nonlinear programming models (MINLP). Finally, a multi criteria decision-making approach is developed to decide the best warehouse type for the six different local markets.