The main objective of this work is to develop an optimization model for the supply chain of a petrochemical company operating under uncertain operating and economic conditions. First, a deterministic model is developed and tested, and then uncertainties in key parameters are introduced. The proposed objective function is based on optimizing the system resources by minimizing the total production costs and raw material procurement, as well as lost demand, backlog, transportation, and storage penalization. A stochastic formulation is then developed, which is based on the two-stage problem method with a finite number of realizations. The optimization model is tested on a typical petrochemical company, manufacturing different grades of polyethylene, operating at a single site and using two reactors. Uncertainties are introduced in demands, market prices, raw material costs, and production yields. The main conclusion of this study is that uncertainties have a dramatic effect on the planning decisions of the petrochemical supply chain. Market demand was found to be the most important parameter, exhibiting a strong impact on the production decisions, followed by the production yields. The stochastic approach was found to be quite effective in handling uncertainties, and the resulting production plans were found to have a rather low expected value of perfect information (EVPI).