Stochastic-fuzzy multi criteria decision making for robust water resources management

Abstract

All realistic Multi Criteria Decision Making (MCDM) problems in water resources management face various kinds of uncertainty. In this study the evaluations of the alternatives with respect to the criteria will be assumed to be stochastic. Fuzzy linguistic quantifiers will be used to obtain the uncertain optimism degree of the Decision Maker (DM). A new approach for stochasticfuzzy modeling of MCDM problems will be then introduced by merging the stochastic and fuzzy approaches into the Ordered Weighted Averaging (OWA) operator. The results of the new approach, entitled SFOWA, give the expected value and the variance of the combined goodness measure for each alternative, which are essential for robust decision making. In order to combine these two characteristics, a composite goodness measure will be defined. By using this measure the model will give more sensitive decisions to the stakeholders whose optimism degrees are different than that of the decision maker. The methodology will be illustrated by using a water resources management problem in the Central Tisza River in Hungary. Finally, SFOWA will be compared to other methods known from the literature to show its suitability for MCDM problems under uncertainty.

Multi-Criteria Decision Making in Civil Engineering. Part Ii – Applications

“…Zarghami and Szidarovszky (2009) presents new approach SFOWA: Ordered Weighted Averaging (OWA) operator with stochastic-fuzzy modelling, and solves an example of recourses management of Central Tisza River in Hungary. Roozbahani et al (2012) suggest PROMETHEE with Precedence Order in the Criteria (PPOC) with application to group water management decisions for urban water supply systems.…”

An Improved Fuzzy Borda Count and its Application to Watershed Management

“…There are a lot of methods to determine the weights of criteria [1][2][3][4][5][6][7], and Xu [7] summarized different methods to obtain the order weights. Generally, they can be divided into three categories.…”

Multistage scenario-based interval-stochastic programming for planning water resources allocation

“…Consequently, in the past decades, many inexact optimization methods were advanced for addressing uncertainties presented as different formats in water resources management systems (Slowinski 1986;Camacho et al 1987;Morgan et al 1993;Srinivasan and Simonovic 1994;Curi et al 1995;Rangarajan 1995;Chang et al 1996a, b;Dupačová et al 1991;Russell and Campbell 1996;Huang 1996Huang , 1998ReVelle 1999;Anderson et al 2000;Jairaj and Vedula 2000;Edirisinghe et al 2000;Watkins et al 2000;Seifi and Hipel 2001;Ji and Chang 2005;Maqsood et al 2005;Li et al 2007a; Guo and Huang 2008;Zarghami and Szidarovszky 2008). Among them, a number of chance-constrained programming (CCP) and multistage stochastic programming (MSP) methods were developed for decision problems whose coefficients (input data) are uncertain but can be represented as chances or probabilities.…”