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Optimal Control of Industrial Pollution under Stochastic Differential Models

Author

Listed:
  • Lu Xiao

    (School of Management, Jiangsu University, Zhengjiang 212013, China)

  • Huacong Ding

    (School of Management, Jiangsu University, Zhengjiang 212013, China)

  • Yu Zhong

    (School of Management, Jiangsu University, Zhengjiang 212013, China)

  • Chaojie Wang

    (School of Mathematical Science, Jiangsu University, Zhengjiang 212013, China)

Abstract

Considering that the amount of waste generated by an industrial enterprise is affected by many uncertain factors, such as the quality of raw materials and the state of equipment. The process is not deterministic, as assumed in most existing studies. In this paper, we propose a stochastic impulse control model to characterize the process of pollution control. The Quasi-Variational Inequality (QVI) method is implemented to solve the optimization problem. Our results show that the optimal control strategy for an industrial enterprise is to perform at a fixed intensity when the pollution reaches the threshold level. In addition, sensitivity analysis of parameters is implemented to illustrate the impact of higher growth rates and volatility on the optimal control strategy. The paper provides a decision basis for industrial enterprises to do pollution control efficiently.

Suggested Citation

  • Lu Xiao & Huacong Ding & Yu Zhong & Chaojie Wang, 2023. "Optimal Control of Industrial Pollution under Stochastic Differential Models," Sustainability, MDPI, vol. 15(6), pages 1-16, March.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:5609-:d:1104718
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    References listed on IDEAS

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