New decision support system for strategic planning in process industries: computational results

Abstract

The impact of a Stochastic Linear Programming (SLP) based Decision Support System in a manufacturing company, such as an integrated aluminum plant, is measured by two important parameters, the VSS and EVPI. With the real data of an integrated steel plant in India, we demonstrate that SLP based DSS can be very effective in managing demand uncertainty and performing futuristic integrated planning, and their financial impact can be in millions of dollars. A two stage stochastic programming model with recourse is implemented in the DSS here. A set of experiments is conducted. Real data from an aluminum company is used to validate the system. The importance of SLP based DSS can be realized from the fact that the value of the stochastic solution (VSS) is USD 3.58 million with 30% demand variability and equally likely demand distribution. The VSS as a percentage of Expectation of Expected Value (EEV) ranges from 0.90% to 18.93% across experiments.