Multi-level production planning in a petrochemical industry using elitist Teaching–Learning-Based-Optimization

• Efficient strategy to determine optimal production plans in a multi-level scenario.
• Proposed strategy leads to better results than the existing results in literature.
• Performance of elitist TLBO on problems with more than 100 variables and constraints.
• Proposed strategy requires less than 45 s for each run.

The complex nature of the petrochemical industries necessitates an efficient decision on a large number of factors so as to optimally operate a plant. Production planning is an integral part of the petrochemical industry and requires the optimal selection of processes, production levels and products to maximize its profit. Previously an MILP formulation has been proposed for guiding the petrochemical industry development in Saudi Arabia (Alfares & Al-Amer, 2002). In this article, we state the limitations of this formulation and propose an alternate elitist TLBO algorithm based strategy to overcome them. The benefits of this strategy include the determination of better production plans that lead to higher profits and have been demonstrated on the eight case studies in the literature. The proposed strategy is generic and can be applied to determine production plans of multiple levels in various industries.