Developing a fuzzy decision support system to determine the location of a landfill site

Abstract

This paper presents two case studies of municipal solid waste site location using a decision-support system based on fuzzy logic. This problem is very complex, as it requires the evaluation of different criteria, which involve environmental, social and economic data. Such data deal with a wide range of information that presents not only quantitative, but also qualitative knowledge. In order to deal with this characteristic, the developed system employs fuzzy rules due to its ability to treat linguistic variables and the human way of thinking. Conventional approaches tend to be less effective in dealing with the imprecise or vague nature of the linguistic assessment. A case study for selecting the location of a new municipal solid waste landfill for the city of Petropolis in Rio de Janeiro is presented. Testing of the proposed method was carried out using data from the municipal solid waste location for another municipality in Rio de Janeiro, Brazil.

System tradeoffs in siting a solar photovoltaic material recovery infrastructure

“…Previous literature has suggested that landfills and recovery facilities avoid locating in industrial or agricultural areas (Basnet et al, 2001;De Feo and De Gisi, 2010;Sharifi et al, 2009;Ş ener et al, 2005) while others encourage the use of these areas (Alves et al, 2009;Gemitzi et al, 2006). Landfill leachate that contains arsenic, selenium, or cadmium has the potential to contaminate soil and crops as well as endanger wildlife flora and fauna.…”

“…The average nearest neighbor index has been used to determine clustering of epidemics, diseases (Delgado et al, 2008;Kan et al, 2008;Lai et al, 2004), natural phenomenon (Bishop, 2010(Bishop, , 2007Guiqin et al, 2009), and population demographic densities (Austin et al, 2005;Çelik et al, 2010;Fisher et al, 2007;Yildiz et al, 2004). It compares the observed mean distance D O between each feature and its nearest neighbor with the expected mean distance D E for a feature in a random pattern (normal distribution) as shown in equation (1) (Alves et al, 2009;Smith et al, 2007). The expected mean distance D E is a function of the total number of features n and the enclosing area A (equation (3)).…”

“…These models include multi-objective decision models that optimize economic and environmental criteria (Bah and Tsiko, 2011;Caruso et al, 1993;Chambal et al, 2003;Erkut et al, 2008;Hokkanen and Salminen, 1997;Nema and Gupta, 1999); whereas single objective models consider economic criteria alone (De Feo and De Gisi, 2010;Hu et al, 2002;Karagiannidis and Moussiopoulos, 1998;Sharifi et al, 2009;Ş ener et al, 2005). Previous work has proposed novel approaches to integrate environmental criteria for example, Caruso et al (1993) (Alves et al, 2009;Caruso et al, 1993) uses scalar weights to optimize both economic, resource waste, and environmental impacts; Nema and Gupta. (1999) links facility technology, risk of an accident, and residue generation in a hazardous waste facility setting; and Vaillancourt and Waaub (2002) includes implicitly spatial data e.g.…”

Identifying problems for choosing suitable areas for installation of a new landfill through GIS technology: A case study

“…For the Brazilian reality, a great governmental effort is occurring, in order to minimize inadequate municipal SW disposal (Alves et al, 2009). In Bauru municipality, located in São Paulo State, this is a critical problem, and the site for the development is our case study in this paper.…”

Municipal Solid Waste Landfill Site Selection using Analytical Hierarchy Process Method and Geographic Information System in Abadan, Iran

“…So, finding suitable land fill site is one of the most significant tasks in SWM (3,4). Recently, there have been different methods reported for landfill site selection such as overlaying GIS digital maps (5,6), integration of fuzzy methodology and GIS (7)(8)(9), weight linear combination (WLC) method and spatial cluster analysis (SCA) (10), combination MCA and GIS methodology (11,12), Integration of GIS and AHP (7,(13)(14)(15)(16)(17)(18), and Intelligent System (19). Siting a landfill requires a combination of social, environmental and technical parameters to locate the areas that will minimize public concerns over health and environmental impacts and will be cost-effective (12).…”