Abdelhak Imoussaten

A Multicriteria Decision Support System using a Possibility Representation for Managing Inconsistent Assessments of Experts Involved in Emergency Situations

Within an emergency unit, the head manager is required to make difficult decisions based on experts’ assessments of many criteria, including personal injuries, environmental impacts, and economic and media consequences. Uncertainty in this collective assessment is related to the multiplicity of experts’ points of view and imprecise assessments. We are proposing a decision support system derived from a situation‐awareness model, generalized herein to the case of multiple actors. It is able of representing, merging, and aggregating expert assessments. Imprecise criteria assessments are first represented by intervals and then merged in the form of a possibility distribution that keeps track of all the information provided, that is, without any loss of information. Next, a Choquet integral based aggregation is carried out to consider the relative importance of criteria and interactions between criteria in the overall assessment of the foreseeable alternatives to get out of the crisis. Finally, a determination of the contributions of each criterion assessment uncertainty to the overall assessment uncertainty provides useful information to the head manager in controlling the decision deliberation by reducing the inconsistent points in the experts’ assessments. The proposals are applied to the emergency issues resulting from a traffic accident occurring at a grade crossing.

Multi-criteria improvement of options

Designing the way a complex system should evolve to better match the customers’ requirements provides an interesting class of applications for muticriteria techniques. The required models to support the improvement design of a complex system must include both preference models and system behavioral models. A MAUT model captures the decisions related to customers’ preferences whereas a fuzzy representation is proposed to model the relationships between systems parameters and performances to capture operational constraints. This latter part of the improvement design is supported by a branch and bound algorithm to efficiently compute the most relevant actions to be performed.

On the consideration of a bring-to-mind model for computing the Information Content of concepts defined into ontologies

Ontologies are core elements of numerous applications that are based on computer-processable expert knowledge. They can be used to estimate the Information Content (IC) of the key concepts of a domain: a central notion on which depend various ontology-driven analyses, e.g. semantic measures. This paper proposes new IC models based on the belief functions theoretical framework. These models overcome limitations of existing ICs that do not consider the inductive inference assumption intuitively assumed by human operators, i.e. that occurrences of a concept (e.g. Maths) not only impact the IC of more general concepts (e.g. Sciences), as considered by traditional IC models, but also the one of more specific concepts (e.g. Algebra). Interestingly, empirical evaluations show that, in addition to modelling the aforementioned assumption, proposed IC models compete with best state-of-the-art models in several evaluation settings.

A Highly Automated Recommender System Based on a Possibilistic Interpretation of a Sentiment Analysis

This paper proposes an original recommender system (RS) based upon an automatic extraction of trends from opinions and a multicriteria multi actors assessment model. Our RS tries to optimize the use of the available information on the web to reduce as much as possible the complex and tedious steps for multicriteria assessing and for identifying users’ preference models. It may be applied as soon as i) overall assessments of competing entities are provided by trade magazines and ii) web users’ critics in natural languages and related to some characteristics of the assessed entities are available. Recommendation is then based on the capacity of the RS to associate a web user with a trade magazine that conveys the same values as the user and thus represents a reliable personalized source of information. Possibility theory is used to take account subjectivity of critics. Finally a case study concerning movie recommendations is presented.

Improving performances in a company when collective strategy comes up against individual interests

In the current industrial context, strategies intended to bring about continuous improvement have to include the multi-criteria performance expression aspects. In complex systems, many actions may be envisaged to achieve the required levels of performance. A fuzzy representation is used to model the relationships between objectives and actions. Mostly, the potential improvement actions are distributed into several departments of a company. Then, the departments have to enter into negotiations to allocate actions‟ responsibility and share the budget granted by the direction. Lots of interest conflicts may occur. An argumentation framework is proposed to model this argumented negotiation for improvement design.

Identifying Criteria Most Influencing Strategy Performance: Application to Humanitarian Logistical Strategy Planning

A growing interest is expressed by organizations for the development of approaches enabling to take advantage of past experiences to improve their decision processes; they may be referred to as Lessons Learned (LL) processes. Within the LL processes implementation framework, the development of semi-automatic approaches able to distinguish criteria having major influence on the evaluation of experiences is crucial for identifying relevant recommendations and performing efficient prescriptive analysis. In this paper, we propose to contribute to LL study by focusing on the definition of an approach enabling, in a specific setting, to identify the criteria most influencing the decision process regarding the overall performance evaluation of a reduced set of experiences. The proposed approach is framed on Multi-Criteria Decision Analysis, and specifically is based on the Electre tri method. In this paper, an illustration of the proposed approach is provided studying the evaluation of logistical response strategies in humanitarian emergency situations.

A text-mining and possibility theory based model using public reports to highlight the sustainable development strategy of a city

Nowadays, ecology and sustainable development are priority governments actions. In Europe, and more specifically in France, sustainable development (SD) is generally broken down into several distinct evaluation criteria. Each criterion is a requirement imposed by the government and corresponds to strategic stakes. When SD improvement actions are financed in an economic region or a city of the French territory by the government, a set of measures is usually set up to assess and control the impact of these actions. More precisely, these measures are used to check whether the region or the city has efficiently invested its budget in respect to the SD strategy of the government. This assessment process is a complex task for the government. Indeed, evaluations are only based on reports provided by the financed regions. These very numerous reports are written in natural language and thus, it is a thorny and time-consuming task for the government to efficiently identify the meaningful information in a plethora of reports and then objectively assess all the expected priorities. This project aims at automating the assessment process from the huge corpus of documents. Text-mining and segmentation techniques are introduced to automatically quantify the attention the region or the city pays to a given criterion. Obviously, this quantification can only be imprecisely determined. Then, the possibility theory is used to merge the information related to each criterion prioritization from all the documents. Finally, an application on the 265 largest cities in France shows the potential of the approach.

A possibilistic framework for identifying the performance to be improved in the imprecise context of preliminary design stage

In a highly competitive and unstable environment, manufacturers must constantly improve their products to remain competitive and satisfy their customers while minimizing incurred costs and risk taking. At the early stages of (re-) engineering, performances forecasting of new product is complicated. Indeed, the impacts of any characteristic change on the product performance are not precisely known. Decision-makers must thus identify the performances to be improved while limiting the engineering efforts spent on innovative upgrades. Although some theoretical worth indexes have been proposed in the multiple criteria literature to estimate the expectable gains when improving changes are planned, they generally rely on non-realistic assumptions on the achievability of the expected improvements. Based on multi-criteria decision analysis techniques and uncertainty theory, this paper proposes an extension of the worth index concept when the likelihood of the expected improvements is not precisely known as it is the case at the preliminary stages of design activities.

A Qualitative Approach to Set Achievable Goals During the Design Phase of Complex Systems

The problem addressed in this paper is “how to set ambitious targets when improving or designing a product while these targets remain within the reach of the manufacturer”. Thus, improvements to be focused on are those which both have a significant positive impact on product performance and correspond to operational changes properly under control by the manufacturer. While some approaches in the literature have already addressed each of the two issues of the improvement problem, few deal with both of them at the same time. In this paper we investigate a qualitative approach that conciliates both points of view as an optimization problem. The notion of interaction between any two objectives to be simultaneously satisfied is central in our framework. An illustrative example related to the design phase of autonomous robot is provided.