Environmental Planning And Management Research Under Uncertainty

Recently, with rapid socio-economic development and improvement in people s living quality, the increasing resources consumption amounts and pressures on environmental could lead to the shortage of the natural resources and the serious environmental pollution problems. Currently, the environmental pollution control measures are advanced from the initial end-of-pipe control to the source control, comprehensive prevention and control. Moreover, the research targets would be shifted from single environmental elements planning to the current integrated planning. With the expansion and in-depth of the research contents and ranges, the optimization methods, which are the main methods within the environmental system analysis theory, also developed from original deterministic methods to the current uncertain methods. These uncertain optimization methods could enhance model reality and applicability. Currently, the uncertain optimization methods could be divided into the following three categories:Stochastic Mathematical Programming, Fuzzy Mathematical Programming and Interval Mathematical Programming. Although they already are applied in environmental planning and management field as well, they also have much space for improvement.In this thesis, the environmental planning problems of the three environmental elements (water, air and waste) would be considered as research objectives. According to the existing problems of the current optimization methodologies, the hybrid optimization models would be obtained through incorporating other optimization methods into the new optimization methods framework (i.e. stochastic robust optimization and fuzzy chance-constrained programming). Specifically, the main research components as follows: (1) A variety of the hybrid models could be generated by incorporating interval linear programming, stochastic chance-constrained programming and two-stage stochastic programming into the stochastic robust optimization framework, respectively. Moreover, they could be used to handle solid waste management and water resource allocation problems. (2) The integrated models could be obtained by integrating the interval linear programming with the fuzzy chance constrained programming (single-sided and double-sided), and they could be used to handle regional air quality management and agricultural water quality management problem, respectively; (3) Considering the Yong Xin County in the Jiang Xi Province as the research objective, the proposed inexact two-stage fuzzy stochastic programming model could be used to genenrate the integrated plans for social, environmental and economic development. The obtained solutions indicated that the proposed model could provide technological support for decision-making and realize the coordinated and sustainable development among the social, economic and environment.The obtained results demonstrated that the new uncertain optimization methods could effectively solve the existing problems of the original uncertain optimization methods; meanwhile, their shortcomings could be remedied through integrating other optimization methods. The proposed optimization models could provide more learning and references for decision-making, also they contributed to the coordinated and sustainable development among the social, economic and environment.