Optimal Control of Industrial Pollution under Stochastic Differential Models

Lu Xiao (), Huacong Ding, Yu Zhong and Chaojie Wang
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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

Sustainability, 2023, vol. 15, issue 6, 1-16

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.

Keywords: industrial pollution; pollution control; stochastic differential equation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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