A Multiobjective Stochastic Optimization Scheme for the Problem of Chemical Production for Sugarcane Companies

Abstract


 
 
 
 This paper presents a multiobjective optimization stochastic scheme for production planning for sugarcane companies under uncertainty. The proposed approach considers three stages. The first stage comprises the mass and energy balances for determining process flows. The second stage considers the formulation of a Multiobjective Deterministic Model (MODM) by considering two objective functions: maximizing the gross margin and minimizing the environmental impact. The MODM is given by different production plans that respond differently to the parameters’ variability under uncertainty. Finally, the last stage considers stochastic elements (i.e., product prices, demands, and costs) within the deterministic scheme to obtain a Multiobjective Stochastic Model (MOSM). A case study’s computational results based on the Colombian sugarcane industry show the proposed scheme’s effectiveness. Results include the investment strategy for optimal production planning with an analysis of the parameters’ uncertainty on the economic performance of the planning production configurations.