Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John's, NL A1B 3X5, Canada.
J Environ Manage. 2011 Apr;92(4):1198-209. doi: 10.1016/j.jenvman.2010.12.013. Epub 2011 Jan 12.
Although many studies on municipal solid waste management (MSW management) were conducted under uncertain conditions of fuzzy, stochastic, and interval coexistence, the solution to the conventional linear programming problems of integrating fuzzy method with the other two was inefficient. In this study, a fuzzy-stochastic-interval linear programming (FSILP) method is developed by integrating Nguyen's method with conventional linear programming for supporting municipal solid waste management. The Nguyen's method was used to convert the fuzzy and fuzzy-stochastic linear programming problems into the conventional linear programs, by measuring the attainment values of fuzzy numbers and/or fuzzy random variables, as well as superiority and inferiority between triangular fuzzy numbers/triangular fuzzy-stochastic variables. The developed method can effectively tackle uncertainties described in terms of probability density functions, fuzzy membership functions, and discrete intervals. Moreover, the method can also improve upon the conventional interval fuzzy programming and two-stage stochastic programming approaches, with advantageous capabilities that are easily achieved with fewer constraints and significantly reduces consumption time. The developed model was applied to a case study of municipal solid waste management system in a city. The results indicated that reasonable solutions had been generated. The solution can help quantify the relationship between the change of system cost and the uncertainties, which could support further analysis of tradeoffs between the waste management cost and the system failure risk.
尽管许多关于城市固体废物管理 (MSW 管理) 的研究是在模糊、随机和区间共存的不确定条件下进行的，但将模糊方法与后两者集成到常规线性规划问题中的常规线性规划解决方案效率低下。本研究通过将 Nguyen 方法与常规线性规划相结合，开发了一种模糊-随机-区间线性规划 (FSILP) 方法，用于支持城市固体废物管理。Nguyen 方法用于通过测量模糊数和/或模糊随机变量的实现值以及三角模糊数/三角模糊随机变量之间的优越性和劣等来将模糊和模糊-随机线性规划问题转换为常规线性规划。所开发的方法可以有效地解决用概率密度函数、模糊隶属函数和离散区间描述的不确定性。此外，该方法还可以改进常规区间模糊规划和两阶段随机规划方法，具有易于实现、约束较少和显著减少消耗时间的优势。该模型应用于一个城市的城市固体废物管理系统案例研究。结果表明，已经生成了合理的解决方案。该解决方案可以帮助量化系统成本变化与不确定性之间的关系，从而支持进一步分析废物管理成本与系统故障风险之间的权衡。
