Fuzzy Stochastic Fractional Programming For Resource And Environmental Systems Management

Over the past decades, the observed impacts caused by global climate disruption as well as water environmental pollution are happening far faster than experts predicted. The increasing utilization of fossil fuels and the unrestrained discharge of pollutants to the water has been considered as the major contributors. Thus, a number of research works have been undertaken to address the conflicting resource, economic and environmental issues in the resource and environmental systems Management problems. However, conventional methods usually combined multiple conflicting objectives into a single one on the basis of subjective or unrealistic assumptions through introducing weighting factors or economic indicators, whose identification was considered difficult. In this study, a fuzzy stochastic dynamic fractional programming (FSFP) method is proposed for supporting sustainable management of resource-environment system under dual uncertainties. It can not only tackle multi-objective issues effectively without setting weights, but also can reflect complicated uncertain parameters expressed as the distribution with fuzzy probability. The developed method can help provide valuable information for supporting in-depth policy analysis of resource and environmental systems management problems. For demonstrating these advantages, FSFP has been applied to the case studies of a typical regional electric power system planning problem and Dongying City’s water resource planning problem, where the decision makers have to deal with conflicts between economic development that maximizes the system profit and environmental protection that minimizes the pollution emissions. The obtained results can help decision makers to identify desired policies under multiple environmental, economic, and constraint-violation conditions.