Multi-objective optimization and evaluation framework for coupled delayed coking and hydrocracking processes based on machine learning

doi:10.1016/j.applthermaleng.2025.129015

Multi-objective optimization and evaluation framework for coupled delayed coking and hydrocracking processes based on machine learning

2025-11-08

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DOI：10.1016/j.applthermaleng.2025.129015

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• XGBoost and NSGA-III with LCA jointly optimize delayed coking and hydrocracking. • Aspen HYSYS mechanistic data calibrate the surrogate and reflect operability limits. • Optimization attains 64.7 wt% conversion and doubles diesel yield with lower impacts.

Multi-objective optimization and evaluation framework for coupled delayed coking and hydrocracking processes based on machine learning

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