designing a multi-objective programming model for hydrocarbon products using a fuzzy credibility-constrained programming-benders decomposition algorithm

The hydrocarbon supply chain (hcsc) is integral to the world economy. this chain includes petroleum products extraction, refinement, distribution, and consumption. considering the importance of planning hcsc for the chain’s activities, it is necessary to simultaneously review and optimize these activities by incorporating important and influential factors. the problem considered in this research has three objectives: 1) maximizing profits, 2) minimizing withdrawal from reservoirs, and 3) minimizing greenhouse gas emissions. the results demonstrated that the profit level in a specific time (10 periods) improved by 18% compared to the current point. in addition, a numerical example was used to simulate distribution, refinement, and extraction locations as a supply chain for petroleum products. finally, the sensitivity analysis revealed that the optimization results are robust to parameter changes and can further improve the optimization of the oil and gas supply chain by maintaining different balances (e.g., natural resources) and reducing environmental effects. interactive fuzzy programming based on credibility criteria was applied to address the parameter uncertainty. further, to reduce the problem’s computational complexity and produce valid and reliable optimal pareto cuts, the benders decomposition method has been employed, which has led to the production of efficient solutions.