Year-end Sale % OFF 
Abstract
We consider a problem of multi-decision sorting subject to multiple criteria. In the newly formulated decision problem, besides performances on multiple criteria, alternatives get evaluations on multiple interrelated decision attributes involving preference-ordered classes. We propose a dedicated method for dealing with such a problem, incorporating a threshold-based value-driven sorting procedure. The Decision Maker (DM) is expected to holistically evaluate a subset of reference alternatives by indicating the quality or risk level on a pre-defined scale of each decision attribute. Based on these evaluations, we construct a set of interrelated preference models, one for each decision attribute, compatible with intra- and inter-decision constraints imposed by such indirect preference information. We also formulate a new way of dealing with potentially non-monotonic criteria by discovering local monotonicity changes in different performance scale regions. The marginal value functions for criteria with unknown monotonicity are represented as a sum of two value functions assuming opposing preference directions, one non-decreasing and the other non-increasing. This permits to obtain an aggregated marginal value function with an arbitrary non-monotonic shape. The practical usefulness of the approach is demonstrated on a case study concerning risk management related to handling (i.e., production, use, manipulation, and processing) nanomaterials in different conditions. We analyze the expert judgments and discuss the inferred preference models, which can be applied to support health and safety managers in reducing the possible risk associated with the respective exposure scenario.
Highlights
Multiple Criteria Decision Analysis (MCDA) concerns decision problems where a set of alternatives are evaluated on a family of criteria, which represent all relevant, heterogeneous viewpoints on the quality of alternatives [1,2]
Marginal value functions The marginal value functions for the ten criteria and four decision attributes are presented in Figs. 6 and 7
We considered and formalized a new problem of multidecision sorting in Multiple Criteria Decision Analysis
Summary
Multiple Criteria Decision Analysis (MCDA) concerns decision problems where a set of alternatives are evaluated on a family of criteria, which represent all relevant, heterogeneous viewpoints on the quality of alternatives [1,2] Many such decision problems fall into the general category of classification, where the alternatives need to be assigned to distinct classes [3]. UTADIS disaggregates the DM’s assignment examples into marginal value functions and class thresholds separating the consecutive decision classes on a scale of comprehensive value [13,14] This idea was found appealing in such various fields as finance [15], energy management [16], or stock portfolio analysis [17]
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
