Online multi-criteria portfolio analysis through compromise programming models built on the underlying principles of fuzzy outranking

This paper introduces an interactive approach to support multi-criteria decision analysis of project portfolios. In high-scale strategic decision domains, scientific studies suggest that the Decision Maker (DM) can find help by using many-objective optimisation methods, which are supposed to provide values in the decision variables that generate high quality solutions. Even so, DMs usually wish to explore the possibility of reaching some levels of benefits in some objectives. Consequently, they should repeatedly run the optimisation method. However, this approach cannot perform well - in an interactive way - for large instances under the presence of many objective functions. We present a mathematical model that is based on compromise programming and fuzzy outranking to aid DMs in analysing multi-criteria project portfolios on the fly. This approach allows relaxing the problem of rapidly optimising portfolios while preserving the beneficial properties of the DM's preferences expressed by outranking relations. Our model supports the decision analysis on two instance benchmarks: for the first one, a better compromise solution was generated 84% of the runs; for the second one, this ranged from 93% to 97%. Our model was also applied to a real-world problem involving social projects, obtaining satisfactory results. (c) 2021 Elsevier Inc. All rights reserved.

Automated summary

This paper introduces a mathematical model based on compromise programming and fuzzy outranking to support Decision Makers in making real-time decision analysis for multi-criteria project portfolios. The model relaxes the problem of rapidly optimizing portfolios while preserving the beneficial properties of the DM's preferences expressed by outranking relations.