SMAA methods and their applications: a literature review and future research directions
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SMAA methods and their applications: a literature review and future research directions R. Pelissari1,2 · M. C. Oliveira1,3 · S. Ben Amor2 · A. Kandakoglu2 · A. L. Helleno1,3
© Springer Science+Business Media, LLC, part of Springer Nature 2019
Abstract Stochastic multicriteria acceptability analysis (SMAA) is a family of multiple criteria decision making (MCDM) methods dealing with incomplete, imprecise, and uncertain information on the evaluations and preference model parameters. As it provides a general framework that has extensions to deal with various specificities in MCDM problems, the development of SMAA methods and their applications in real-life decision-making problems have been increased over the recent years. This paper provides an up-to-date literature review of different SMAA methods and their applications in various areas. First, we selected, from different on-line data base, 118 articles published between 1998 and 2017. We categorized the selected papers into theoretical and applied. While the theoretical papers were analyzed based on the method’s aggregation procedure, type of problem, type of method’s outputs and inputs, the applied papers were separated and analyzed by application areas. Then, we provide some descriptive statistics, analyzing the papers regarding to publication year and journals of publication. Finally, we provide some guidelines to assist decision-makers in the choice of a SMAA method on a specific decision-making context and some future research directions. Keywords Uncertainty · Imprecision · Multiple criteria decision making (MCDM) · Stochastic multicriteria acceptability analysis (SMAA) · Simulation
1 Introduction Multiple criteria decision making (MCDM), one of the very fast growing areas of operational research, has been successfully applied to many domains for solving problems including multiple conflicting criteria (Mardani et al. 2015a). In real-life MCDM, problems it is common the presence of incomplete, imprecise and uncertain information for both criteria evaluations and the decision makers (DMs) preferences (Stewart 2005; Ben Amor * R. Pelissari [email protected] 1
Faculty of Industrial Engineering, UNIMEP, Santa Bárbara d’Oeste, Brazil
2
Telfer School of Management, University of Ottawa, Ottawa, Canada
3
Engineering School, Mackenzie Presbyterian University, São Paulo, Brazil
13
Vol.:(0123456789)
Annals of Operations Research
et al. 2015). Consequently, many MCDM methods dealing with uncertainty have been proposed in the literature, such as the family of SMAA (stochastic multicriteria acceptability analysis) methods. SMAA method was proposed by Lahdelma et al. (1998) for discrete multiple criteria group decision problems where either criteria measurements or criteria weights are not precisely known. SMAA is based on the idea of computing volumes that applies an inverse weight space analysis in order to describe the criteria weights that make each alternative the most preferred one. SMAA provides descriptive measures calculated trough Mo
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