Fuzzy Multi-Objective Stochastic Models for Municipal Solid Waste Management

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Abstract

With rising urbanization and change in lifestyle and food habits of human beings, the amount of municipal solid wastes (MSWs) are now being increasing day by day, and the composition of wastes are now also being changed. Therefore, it is now becoming essential to develop a consistent mathematical model for managing those wastes in a systematic manner. In this context, fuzzy chance constrained programming (FCCP) model becomes useful to handle wastes efficiently through the process of selecting sorting stations, treatment facilities, etc. through an efficient way so that the net system cost of sorting and transporting the wastes would be minimized, and the revenue generated from different sorting stations and different treatment facilities would be to maximized. From that view point, in this chapter, a fuzzy chance constrained programming (CCP) model is developed for MSW management. Most of the parameters involved with this model are imprecisely defined and probabilistically uncertain. So, the parameters of the objectives are considered as FNs, and the right side parameters of the probabilistic constraints involve normally distributed fuzzy random variables (FRVs). To resolve the cases arising due to the multiple occurrences of fuzzy goals, a fuzzy goal programming (FGP) has been adopted. To expound the potential use of the approach, a modified version of a case example, studied previously, is considered and solved. The achieved model solution is discussed elaborately to illustrate the proposed methodology for MSW management.
城市生活垃圾管理的模糊多目标随机模型
随着城市化进程的加快以及人类生活方式和饮食习惯的改变,城市固体废物的数量日益增加,垃圾的组成也在发生变化。因此,现在至关重要的是发展一个统一的数学模型,以便系统地管理这些废物。在这种情况下,模糊机会约束规划(FCCP)模型可以有效地通过选择分拣站、处理设施等过程来有效地处理废物,使废物的分拣和运输的净系统成本最小化,并使不同分拣站和不同处理设施产生的收益最大化。从这个角度出发,本章建立了城市垃圾管理的模糊机会约束规划(CCP)模型。该模型中涉及的大多数参数都是不精确定义的,并且在概率上是不确定的。因此,将目标参数视为FNs,而概率约束的右侧参数涉及正态分布的模糊随机变量(frv)。为了解决模糊目标多次出现的情况,采用了模糊目标规划(FGP)。为了说明该方法的潜在用途,本文考虑并解决了先前研究过的一个案例的修改版本。详细讨论了实现的模型解决方案,以说明拟议的城市固体废物管理方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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