The weights of the drought risk index （DRI）, which linearly combines the reliability, resiliency, and vulnerability, are difficult to obtain due to complexities in water security during drought periods. Therefore, d...The weights of the drought risk index （DRI）, which linearly combines the reliability, resiliency, and vulnerability, are difficult to obtain due to complexities in water security during drought periods. Therefore, drought entropy was used to determine the weights of the three critical indices. Conventional simulation results regarding the risk load of water security during drought periods were often regarded as precise. However, neither the simulation process nor the DRI gives any consideration to uncertainties in drought events. Therefore, the Dempster-Shafer （D-S） evidence theory and the evidential reasoning algorithm were introduced, and the DRI values were calculated with consideration of uncertainties of the three indices. The drought entropy and evidential reasoning algorithm were used in a case study of the Haihe River Basin to assess water security risks during drought periods. The results of the new DRI values in two scenarios were compared and analyzed. It is shown that the values of the DRI in the D-S evidence algorithm increase slightly from the original results of Zhang et al. （2005）, and the results of risk assessment of water security during drought periods are reasonable according to the situation in the study area. This study can serve as a reference for further practical application and planning in the Haihe River Basin, and other relevant or similar studies.展开更多
In this paper,a holistic hierarchical analytical model is proposed to assess the performance of enablers in an integrated logistics system.Due to the ambiguous and complex environment,various refinements are needed to...In this paper,a holistic hierarchical analytical model is proposed to assess the performance of enablers in an integrated logistics system.Due to the ambiguous and complex environment,various refinements are needed to assess enablers and prioritize for the criteria such as economic,operational,and environment.The proposed hierarchical model is developed by a systematic approach that includes fuzzy analytical hierarchy process(FAHP),triangular fuzzy numbers(TFN),an evidential reasoning algorithm(ERA),and expected utility theory(EUT).The FAHP is used to analyze and obtain the weights of the criteria by considering the expert’s opinions.ERA is used to synthesize the enablers based on the selected criteria.These enablers are represented using subjective assessment along with a set of evaluation grades for a qualitative attribute.EUT helps in obtaining crisp values of enablers for their performance estimation.With these set of methodologies,a hierarchical model is proposed that prevent low flexibility and inadequate appropriateness of the proposed model.Further,the model helps in scenario generation for the logistics professionals who are facing various problems in integrating logistics and incorporating sustainability due to lack of appropriate methodologies and evaluation techniques.Finally,sensitivity analysis is used for overall model validation.展开更多
基金supported by the National Natural Science Foundation of China(Grants No.51190094,50909073,and 51179130)the Hubei Province Natural Science Foundation(Grant No.2010CDB08401)
文摘The weights of the drought risk index （DRI）, which linearly combines the reliability, resiliency, and vulnerability, are difficult to obtain due to complexities in water security during drought periods. Therefore, drought entropy was used to determine the weights of the three critical indices. Conventional simulation results regarding the risk load of water security during drought periods were often regarded as precise. However, neither the simulation process nor the DRI gives any consideration to uncertainties in drought events. Therefore, the Dempster-Shafer （D-S） evidence theory and the evidential reasoning algorithm were introduced, and the DRI values were calculated with consideration of uncertainties of the three indices. The drought entropy and evidential reasoning algorithm were used in a case study of the Haihe River Basin to assess water security risks during drought periods. The results of the new DRI values in two scenarios were compared and analyzed. It is shown that the values of the DRI in the D-S evidence algorithm increase slightly from the original results of Zhang et al. （2005）, and the results of risk assessment of water security during drought periods are reasonable according to the situation in the study area. This study can serve as a reference for further practical application and planning in the Haihe River Basin, and other relevant or similar studies.
文摘In this paper,a holistic hierarchical analytical model is proposed to assess the performance of enablers in an integrated logistics system.Due to the ambiguous and complex environment,various refinements are needed to assess enablers and prioritize for the criteria such as economic,operational,and environment.The proposed hierarchical model is developed by a systematic approach that includes fuzzy analytical hierarchy process(FAHP),triangular fuzzy numbers(TFN),an evidential reasoning algorithm(ERA),and expected utility theory(EUT).The FAHP is used to analyze and obtain the weights of the criteria by considering the expert’s opinions.ERA is used to synthesize the enablers based on the selected criteria.These enablers are represented using subjective assessment along with a set of evaluation grades for a qualitative attribute.EUT helps in obtaining crisp values of enablers for their performance estimation.With these set of methodologies,a hierarchical model is proposed that prevent low flexibility and inadequate appropriateness of the proposed model.Further,the model helps in scenario generation for the logistics professionals who are facing various problems in integrating logistics and incorporating sustainability due to lack of appropriate methodologies and evaluation techniques.Finally,sensitivity analysis is used for overall model validation.
