Addressing the Location of Undesirable Facilities through the Dominance‐based Rough Set Approach

Abstract

The location problems of the so-called undesirable facilities such as waste incinerators or landfills presents two main characteristics: (i) social opposition and (ii) a huge number of social, economic and environmental data that have to be taken into account. In this sense, the decision problem can be seen as an intrinsically complex problem because it involves different interconnected elements and must achieve objectives that are often in conflict.The work proposes the use of the theory of the dominance-based rough set approach (DRSA). The DRSA is a development of the rough sets philosophy which concerns the possibility of extending this theory to multiple criteria decision analysis by providing the model with preference-ordered aspects of the problem.This article presents an argument for the use of DRSA in decisions-aiding processes concerning urban and territorial projects. Mention has to be made to the fact that there are very few applications of DRSA to real case studies, and in particular, there is no application concerning the localization of undesirable facilities. Given the very delicate nature of the problem, where the contrasts are not only theoretical but also concrete, it is essential to 'test' the various methods of decision support before using them in real contexts. In this article, we argue that a simulation phase should reclaim responsibility for reliability and validity by implementing verification and self-correcting strategies during the development of the application itself.In particular, the paper presents an application to a real-world problem, concerning the choice of the location for a waste incinerator in the Province of Turin (Italy). In the application, different sites are analysed and compared through the use of the DRSA on the basis of different attributes, such as presence of population, hydrogeological risk, landscape value, interferences on transport infrastructures.

Leveraging energy efficiency to finance public-private social housing projects

“…Over the span of the last three decades, the RS approach has been applied to explore, interpret and extract data in a variety of fields (Pawlak, 1998), from medical diagnoses to engineering application (Pawlak and Skowron, 2007b). Further developments have led to the use of RS as a tool to treat incomplete or imprecise information systems (Kryszkiewicz, 1998;Greco et al, 1999;Dembczyński et al, 2009), and also as a multicriteria decision support tool (Pawlak, 1997;Greco et al, 2000Greco et al, , 2001Greco et al, , 2002Abastante et al, 2013Abastante et al, , 2014. RS analyses have already been carried out to investigate the feasibility drivers of urban renewal transactions, particularly those implemented through PPPs (Nijkamp et al, 2002;Stanghellini and Copiello, 2011).…”

A new decision-making approach for multiple criteria sorting with an imbalanced set of assignment examples

“…Although existing MCS methods have shown great success in many real-world applications [26,27,28,29,30,31,32,33,34,35,36,37,38], the complexity of some practical problems makes them inadequate to achieve a satisfactory assignment recommendation. One noteworthy difficulty is the imbalanced distribution of alternatives among considered categories, which exists in a wide range of real-world applications.…”

Multi-criteria decision making to support waste management: A critical review of current practices and methods

“…Concerning the combination of MCDM methods with geographic information system (GIS) tools, for Tavares et al (2011), which used this approach for waste facility location, the integration of these techniques offers a powerful tool to facilitate and accelerate any siting process. In fact, GIS methods are valuable for applications that involve data dependent on geographic position, because they offer adequate functionalities to capture, store, check, manipulate, and process spatially referenced data (Abastante et al, 2014;Chiueh et al, 2008). Among the articles recorded, it was noted that 44% of the facility location studies combined MCDM and GIS, whereas this combination was observed only in 2% of WM strategy articles.…”

“…It is noted that, owing to the low number of articles dedicated to the location of treatment facilities other than landfill, there is no consensus about criteria to assess them. In fact, among the MCDMrecorded articles linked to incineration location (Abastante et al 2014;Bottero & Ferretti 2010;Chang et al 2009;Chiueh et al 2008;Tavares et al 2011;Wey 2005), a high diversity of criteria was noted. So, considering the applicability of MCDM in facility location and the lack of a disseminated methodology dedicated to supporting siting waste technologies other than landfilling, studies involving different types of treatment facilities is a recommended topic for future investigation.…”