Li Yongping, Huang Guohe
College of Urban and Environmental Sciences, Peking University, Beijing, People's Republic of China.
J Air Waste Manag Assoc. 2009 Mar;59(3):279-92. doi: 10.3155/1047-3289.59.3.279.
In this study, a dynamic analysis approach based on an inexact multistage integer programming (IMIP) model is developed for supporting municipal solid waste (MSW) management under uncertainty. Techniques of interval-parameter programming and multistage stochastic programming are incorporated within an integer-programming framework. The developed IMIP can deal with uncertainties expressed as probability distributions and interval numbers, and can reflect the dynamics in terms of decisions for waste-flow allocation and facility-capacity expansion over a multistage context. Moreover, the IMIP can be used for analyzing various policy scenarios that are associated with different levels of economic consequences. The developed method is applied to a case study of long-term waste-management planning. The results indicate that reasonable solutions have been generated for binary and continuous variables. They can help generate desired decisions of system-capacity expansion and waste-flow allocation with a minimized system cost and maximized system reliability.
在本研究中，开发了一种基于不精确多阶段整数规划（IMIP）模型的动态分析方法，以支持不确定性条件下的城市固体废物（MSW）管理。区间参数规划和多阶段随机规划技术被纳入整数规划框架内。所开发的IMIP能够处理以概率分布和区间数表示的不确定性，并能在多阶段背景下反映废物流分配决策和设施容量扩展方面的动态变化。此外，IMIP可用于分析与不同经济后果水平相关的各种政策情景。所开发的方法应用于一个长期废物管理规划的案例研究。结果表明，已为二元变量和连续变量生成了合理的解决方案。它们有助于以最小化的系统成本和最大化的系统可靠性生成系统容量扩展和废物流分配的理想决策。
