Extension of the ELECTRE III Method to the Case of Uncertain Preferences: Application to an Example of the Environmental Management Problem

Mohammed Chaouki Abounaima,Fatima-Zahra El Mazouri,Mohammed Chaouk Talibi Alaoui,Mohamed Ouzarf,Loubna Lamrini

doi:10.19139/soic-2310-5070-1194

Abstract

Almost all the decision problems are by nature multi-criteria, where multiple and conflflicting criteria must be considered in the decision-making process. For some cases of these decision problems, they are further marked by a lack of certainty and precision in the decision-maker’s judgments and preferences. This study aims to propose an extension of the ELECTRE III method, widely used in the multi-criteria decision aid fifield, to the case of a decision problem where the decision-maker preferences are imprecise and uncertain. In this proposed adaptation, the inaccuracies and uncertainties will be expressed by an uncertainty interval. The proposed extension will be tested with an example problem to demonstrate its feasibility and relevance. In this example of environmental management, we propose to rank three oil refifinery installation projects from the best project to the worst project. The experiment results show that the ELECTRE III method extension can be used easily and rigorously when the uncertainty intervals express the decision-maker’s preferences. Finally, the results obtained in this work can be extended to other multi-criteria analysis methods.

Highlights

For more than five decades, multiple multi-criteria decision aid methods have emerged, ranging from the family of weighted sum methods, the best known and used, to the family of outranking methods
Numerous decision-making problems require taking into account the conflicting views, uncertainties, and imprecise judgment of decision-makers
This paper has proposed a new approach inspired by the same calculation process used in the ELECTRE III method, but it supports uncertain and imprecise preferences

Summary

Introduction

For more than five decades, multiple multi-criteria decision aid methods have emerged, ranging from the family of weighted sum methods, the best known and used, to the family of outranking methods. Each method family has its advantages and disadvantages. All these methods, called Multi-Criteria Aggregation Procedures (MCAPs)[1], assume that the decision-maker (DM) disposes of certain preferences, so the DM is asked to express the judgments clearly and without any uncertainty and imprecision. In many real-life situations, these preferences, as well as the judgment values, cannot be provided with precision and certainty. It is empirically demonstrated that decision-maker’s judgment often has vague and ambiguous preferences and cannot be estimated with a precise and unique value.

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