Production scheduling optimization model of crude oil industry chain considering volatility constraints
Production scheduling optimization models for crude oil industry in the supply chain typically focus on specific segments and aim to minimize overall costs through single-objective linear programming.This study presented a comprehensive and systematic multi-objective optimization model for production scheduling,accurately characterizing various stages in the entire crude oil supply chain.The ε-constraint method was employed to solve the model.To address the issue of inaccurate capturing of processing and transportation fluctuations in traditional scheduling models,this study introduced auxiliary variables and constraints to penalize volatility factors.This approach effectively reduced fluctuations in processing and transportation volumes within each period,bringing the model solutions closer to actual scheduling scenarios.The results demonstrated that the proposed optimization model,incorporating volatility constraints,achieved a more desirable overall cost value while meeting practical scheduling requirements.
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