A multi-objective optimization method for industrial value chain under carbon risk

With the implementation of the dual carbon policy, the owner enterprise in industrial value chain is faced with risks associated with uncertainties such as carbon emission limits and trading policies. The risks directly affect the stability and balance between economic and environmental objectives, causing a security issue in the industrial value chain. To address this issue, a multi-objective optimization method for industrial value chain under carbon risk is proposed. First, we establish a multi-objective industrial value chain model that optimizes economic and environmental objectives and consider the resistance of the members of industrial value chain to carbon risk. Second, to solve the model, a dynamic multimodal difference algorithm is proposed. It monitors the changes in carbon risk dynamically and obtains Pareto solutions for the multi-objective model. Finally, we conduct simulation experiments on the industrial value chain of an automobile at different scales. The experimental results show that the decrease in economic and environmental objectives is reduced by 28% and 62% compared to the fuzzy model, respectively. In addition, compared to the MOEA/D, the economic objective increases by 11%, and the environmental objective decreases by 32%. The method achieves stability and balance between economic and environmental objectives under carbon risk, ensuring the security of the industrial value chain.