Mining activities may cause serious damages to the river ecological environment in mining areas. It has been realized that challenging is faced for optimal decision-making on the river ecological restoration resulting...Mining activities may cause serious damages to the river ecological environment in mining areas. It has been realized that challenging is faced for optimal decision-making on the river ecological restoration resulting from system complexity, multi-objectives, long term restoration in which multiple stages may be needed to take, and difficulty in detailed process quan- tification. By analyzing and fully reflecting the differences between the central zone and surrounding zones of the restored river passing through the mining area, the comprehensive evaluation index systems of the central zone and surrounding zones are separately suggested firstly. Then a scenario-based optimization decision-making model for river ecological restoration in min- ing areas was established with taking advantages of spatial divisions and following procedure of first going through optimiza- tion by sub-region level, then optimizing by integration. Then, a framework for scenario-based optimal decision-making on water-deficient river ecological restoration in mining areas is proposed in which a multi-objective and multi-stage spatial division optimization method is considered to improve decision-making efficiency and enhance its practicability. It is indicated that this optimization framework is reasonable and practical, which is expected to offer reliable decision support in identifying the effective solutions on optimal management of the water-deficient river ecological restoration in mining areas. At the same time, it has implications in general land reclamation and ecological restoration in the mining areas.展开更多
The technology investment strategy under uncertainty is the key subject. However, the expected utility maximization often employed as the decision process fails to consider the high risk with low probability cases. On...The technology investment strategy under uncertainty is the key subject. However, the expected utility maximization often employed as the decision process fails to consider the high risk with low probability cases. On the other hand, the existing min-max regret strategy tends to be dominated by the ＂worst assumption＂ regardless of its probability. This research proposes a new framework by formulating the regret by the Minkowski＇s generalized distance. The authors then apply the formulation to the IAM （integrated assessment model） MARIA. This study focuses on the uncertainties of CCS （carbon capture and storage） costs and the global warming damages. This formulation is then extended to the multi-stage decision frame, known as ATL （act-then-learn） method. The simulation results suggest that the substantial changes in CCS and nuclear deployment strategies depending on the future uncertainty scenarios. The results also suggest that the minimum regret strategy favors the capital accumulation in the early stage.展开更多
文摘Mining activities may cause serious damages to the river ecological environment in mining areas. It has been realized that challenging is faced for optimal decision-making on the river ecological restoration resulting from system complexity, multi-objectives, long term restoration in which multiple stages may be needed to take, and difficulty in detailed process quan- tification. By analyzing and fully reflecting the differences between the central zone and surrounding zones of the restored river passing through the mining area, the comprehensive evaluation index systems of the central zone and surrounding zones are separately suggested firstly. Then a scenario-based optimization decision-making model for river ecological restoration in min- ing areas was established with taking advantages of spatial divisions and following procedure of first going through optimiza- tion by sub-region level, then optimizing by integration. Then, a framework for scenario-based optimal decision-making on water-deficient river ecological restoration in mining areas is proposed in which a multi-objective and multi-stage spatial division optimization method is considered to improve decision-making efficiency and enhance its practicability. It is indicated that this optimization framework is reasonable and practical, which is expected to offer reliable decision support in identifying the effective solutions on optimal management of the water-deficient river ecological restoration in mining areas. At the same time, it has implications in general land reclamation and ecological restoration in the mining areas.
文摘The technology investment strategy under uncertainty is the key subject. However, the expected utility maximization often employed as the decision process fails to consider the high risk with low probability cases. On the other hand, the existing min-max regret strategy tends to be dominated by the ＂worst assumption＂ regardless of its probability. This research proposes a new framework by formulating the regret by the Minkowski＇s generalized distance. The authors then apply the formulation to the IAM （integrated assessment model） MARIA. This study focuses on the uncertainties of CCS （carbon capture and storage） costs and the global warming damages. This formulation is then extended to the multi-stage decision frame, known as ATL （act-then-learn） method. The simulation results suggest that the substantial changes in CCS and nuclear deployment strategies depending on the future uncertainty scenarios. The results also suggest that the minimum regret strategy favors the capital accumulation in the early stage.
