Affiliations: [a] School of Economics and Management, University of Science and Technology Beijing, Beijing, China
| [b] School of Mathematics, Pyongyang University of Mechanical Engineering, Pyongyang, D P R of Korea
| [c] School of Economics, Zhengzhou University of Aeronautics, Henan, Zhengzhou, China
Correspondence:
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Corresponding author. Xiaoxia Huang, School of Economics and Management, University of Science and Technology Beijing, Beijing, 100083, China. E-mail: hxiaoxia@manage.ustb.edu.cn.
Abstract: To achieve the carbon neutrality goal, enterprises should consider not only the development of new low-carbon emission projects but also the adjustment of the existing high-carbon emission projects. This paper discusses a multi-period project adjustment and selection (MPPAS) problem under the carbon tax and carbon quota policies. First, we propose an uncertain mean-chance MPPAS model for maximizing the profit of the project portfolio under the carbon tax and carbon quota policies. Then, we provide the deterministic equivalent of the proposed model and conduct the theoretical analysis of the impact of carbon tax and carbon quota policies. Next, we propose an improved adaptive genetic algorithm to solve the proposed model. Finally, we give numerical experiments to verify the proposed algorithm’s performance and show the proposed model’s applicability. Research has shown that the government can achieve the carbon neutrality goal by determining reasonable carbon tax and carbon quota policies, and companies can make the optimal investment decisions for the project portfolio by the proposed model. In addition, the proposed algorithm has good performances in robustness, convergence speed, and global convergence.
