摘要
针对空气质量管理系统存在的多重不确定性与复杂性,基于区间线性规划(ILP)、随机数学规划(SMP)和模糊可能性规划(FPP)方法,研究开发了区间随机模糊可能性规划(ISFPP)模型以实现有效管理政策的制订。开发的ISFPP模型不仅能够处理多重不确定性,而且能够反映系统复杂性。同时,ISFPP模型能够分析不同置信水平下的管理情景。将ISFPP模型应用到一个假设的空气质量管理案例中,结果表明,置信水平的变化,可能导致系统总成本、污染物处理量及超标排放量发生相应的变化;在不同的置信水平下,生产企业能够选择合适的污染物控制措施,确定合理的污染物处理量和超标排放量。因而,模型结果能够用于生成决策方案,进而帮助决策者制订有效的管理政策。
In air quality management systems, aiming at the existence of multiple uncertainties and system complexities,based on the methods of interval linear programming（ ILP）,stochastic mathematical programming（ SMP） and fuzzy possibilistic programming（ FPP）,an interval stochastic fuzzy possibilistic programming（ ISFPP）model was developed to identify effective management policies. The developed ISFPP model can not only deal with multiple uncertainties,but also reflect system complexities. Moreover,the ISFPP model can help to analyze various management scenarios associated with different confidence levels. The ISFPP model was applied to a hypothetical case study of air quality management. The results indicate that the change of confidence level may lead to the corresponding changes of total system cost,treatment amounts of pollutants and emission amounts exceeding the standards; moreover,under different confidence levels,different enterprises can select the appropriate pollutant control measures and determine the reasonable treatment amounts of pollutants and emission amounts exceeding the standards. Thus,the modeling results can be used for generating decision alternatives,and help the decisionmakers to identify desired management policies.
出处
《环境工程技术学报》
CAS
2015年第2期97-105,共9页
Journal of Environmental Engineering Technology
关键词
空气质量管理
优化模型
区间线性规划
随机数学规划
模糊可能性规划
不确定性
air quality management
optimization model
interval linear programming
stochastic mathematical programming
fuzzy possibilistic programming
uncertainty
