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AbstractThis paper presents Interactive Robustness analysis and parameters' Inference for multicriteria Sorting problems (IRIS), a Decision Support System (DSS) designed to sort actions (projects, candidates, alternatives, clients, etc.) described by their performances on multiple criteria into an ordered set of categories defined a priori. It is based on the ELECTRE TRI sorting method, but does not require the decision maker (DM) to indicate precise values for all of the method's parameters. More realistically, the software expects the DM to indicate some constraints that these parameters should respect, including sorting examples that the program should reproduce. If the constraints indicated by the DM do not contradict each other (i.e. form a consistent system), then IRIS infers a combination of parameter values that reproduces all the sorting examples, indicating also the range of possible assignments of actions to categories that would be possible without violating any of the stated constraints. If the constraints are contradictory (i.e. form an inconsistent system), then IRIS suggests a combination of parameter values that minimizes an error function and identifies alternative ways to restore the system's consistency by removing some constraints. Copyright © 2005 John Wiley & Sons, Ltd.

This paper outlines a distributed GDSS suitable to be used over the Internet, based on the VIP Analysis methodology and software. VIP Analysis incorporates complementary approaches to deal with the aggregation of multicriteria performances by means of an additive value function under imprecise information. This proposed GDSS intends to support a decision panel forming a democratic decision unit, whose members wish to reach a final decision in a choice problem, based on consensus or on some majority rule. Its purpose is not to impose an aggregated model from the individual ones. Rather, the GDSS is designed to reflect to each member the consequences of his/her inputs, confronting them with analogous reflections of the group members' inputs. We propose aggregation procedures to provide a reflection of the group's inputs to each of its members, and an architecture for a GDSS implementing these procedures. ; http://www.sciencedirect.com/science/article/B6VCT-4B5JR15-7/1/ec69930c867d6cea3058a818f9f33fe7

This paper is a systematic review of studies that used multicriteria decision analysis (MCDA) to address plastic waste management. A literature search for scientific articles in online databases (Web of Science and Scopus) enabled us to identify 20 relevant papers from 2008 to 2021, spanning case studies in three continents. These studies focus on: plastics as a resource (material), plastics as a product (reverse logistics), and plastics as a problem (pollution). Content analysis methodology was used, with the focus being on how the authors used MCDA for managing plastic waste, which has relevance for researchers and practitioners. Alternative solutions were found for the selection of disposal methods for almost all types of plastic categorized in this review. The most popular method was AHP, followed by TOPSIS, outranking methods, MAUT/MAVT and simple weighted sums, with some studies including more than one method. The choice of criteria spanned operational (mostly), but also environmental and economic aspects to evaluate the alternatives. Less frequently, one finds criteria related to social, managerial, and political aspects. The weighting of the criteria was performed mainly by consulting experts, followed by decision makers. Representatives of the affected population or other stakeholders have been consulted only on a few occasions. The authors of the studies consider their application of MCDA was successful, highlighting mainly the importance of being able to encompass different dimensions in the evaluation of the alternatives and the transparency of the process. In most cases, a winning alternative emerged clearly, which sometimes was a combination of multiple strategies. We also report other recommendations of these authors concerning marine and terrestrial plastic waste management.