Postoptimal analysis in a multi-attribute decision model for restoring contaminated aquatic ecosystems

• Published in: The Journal of the Operational Research Society Vol. 52; no. 7; pp. 727 - 738
• Main Authors: Mateos, A, Ríos-Insua, S, Gallego, E
• Format: Journal Article
• Language: English
• Published: Basingstoke Taylor & Francis 01.07.2001; Macmillan Press; Palgrave; Taylor & Francis Ltd
• Subjects: Applied sciences; aquatic ecosystem; Aquatic ecosystems; Aquatic life; Assessed values; Case-Oriented Papers; Decision analysis; Decision making models; Decision support systems; Decision theory. Utility theory; Economic costs; Ecosystem models; Ecosystems; Exact sciences and technology; Hierarchies; Lentic systems; Mathematical models; multi-attribute additive value; Musical intervals; Operational research and scientific management; Operational research. Management science; Operations research; Radioactive wastes; radionuclide contamination; Radionuclides; Sensitivity analysis; Studies; System evaluation; Sensitivity analysis; Decision making; Decision analysis; Modeling; Optimization; Aggregation; Drainage; Scaling function; Aquatic environment; Optimal strategy; Ecosystem; Robustness; Value analysis
• ISSN: 0160-5682; 1476-9360
• DOI: 10.1057/palgrave.jors.2601156

We describe the evaluation module of the MOIRA system, developed to identify optimal remedial strategies for restoring radionuclide contaminated aquatic ecosystems and drainage areas. This module includes a multiparametric sensitivity analysis, which is based on a multi-attribute additive value model, aimed at identifying optimal remedial strategies for restoring aquatic ecosystems contaminated by radionuclides. We introduce the sensitivity analysis to check the robustness of the conclusions on the inputs. This provides insights into the problem in the sense of making better use of the available information. This analysis is focused on judgemental inputs, imprecise value functions on attributes and imprecise scaling factors or weights for their aggregation. These are of utmost importance in determining the optimal countermeasures.