Dynamic optimal strategies in transboundary pollution game under learning by doing

被引：42
作者：
Chang, Shuhua [1 ]
Qin, Weihua [1 ,2 ]
Wang, Xinyu [1 ]
机构：
[1] Tianjin Univ Finance & Econ, Coordinated Innovat Ctr Computable Modeling Manag, Tianjin 300222, Peoples R China
[2] Hebei Univ Technol, Sch Sci, Tianjin 300401, Peoples R China
来源：
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS | 2018年 / 490卷
基金：
中国国家自然科学基金;
关键词：
Transboundary pollution game; Emission permits trading; Abatement policy; Learning by doing; DIFFERENTIAL GAME; ABATEMENT;
D O I：
10.1016/j.physa.2017.08.010
中图分类号：
O4 [物理学];
学科分类号：
0702 ;
摘要：
In this paper, we present a transboundary pollution game, in which emission permits trading and pollution abatement costs under learning by doing are considered. In this model, the abatement cost mainly depends on the level of pollution abatement and the experience of using pollution abatement technology. We use optimal control theory to investigate the optimal emission paths and the optimal pollution abatement strategies under cooperative and noncooperative games, respectively. Additionally, the effects of parameters on the results have been examined. (C) 2017 Elsevier B.V. All rights reserved.
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页码：139 / 147
页数：9
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