The Economic Evaluation of Projects as a Structuring Discipline of Learning Processes to Support Decision-Making in Sustainable Urban Transformations

This paper is based on the following research questions: i) In which way could the discipline Economic Evaluation of Projects contribute to conveying the sustainability concept in urban settings among master’s degree students? What are the methods/techniques that can support decision processes of sustainable urban transformation? In response to the two research questions, the paper proposes a multi-methodological framework as a design tool for students (future professionals) aimed at representing the decision problem from a sustainable planning perspective. Through a Problem-Based Learning approach based on a case study, the proposed framework considers: SWOT Analysis, Stakeholder Analysis (SA), Multicriteria Analysis (MCDA), Cash Flow Analysis (CFA), and the application of the Neighborhood Sustainability Assessment Tools (NSATools). The multi-methodological framework has been applied to an experimental teaching case study as part of the Economic Evaluation of Projects module demonstrating its effectiveness in terms of sustainable spatial planning and structuring of the decision process from a multi-actor perspective. Future directions of the research are aimed at tackling two major limitations of the multi-methodological framework as the need to closely reflect a real decision process through an iterative framework and the sometimes hard interpretation of some elements of urban sustainability

Building a binary outranking relation in uncertain, imprecise and multi-experts contexts: The application of evidence theory

AbstractWe consider multicriteria decision problems where the actions are evaluated on a set of ordinal criteria. The evaluation of each alternative with respect to each criterion may be uncertain and/or imprecise and is provided by one or several experts. We model this evaluation as a basic belief assignment (BBA). In order to compare the different pairs of alternatives according to each criterion, the concept of first belief dominance is proposed. Additionally, criteria weights are also expressed by means of a BBA. A model inspired by ELECTRE I is developed and illustrated by a pedagogical example

A Systematic Approach to the Management of Military Human Resources through the ELECTRE-MOr Multicriteria Method

Personnel selection is increasingly proving to be an essential factor for the success of organizations. These issues almost universally involve multiple conflicting objectives, uncertainties, costs, and benefits in decision-making. In this context, personnel assessment problems, which include several candidates as alternatives, along with several complex evaluation criteria, can be solved by applying Multicriteria Decision Making (MCDM) methods. Uncertainty and subjectivity characterize the choice of personnel for missions or promotions at the military level. In this paper, we evaluated 30 Brazilian Navy officers in the light of four criteria and 34 subcriteria. To support the decision-making process regarding the promotion of officers, we applied the ELECTRE-Mor MCDM method. We categorized the alternatives into three classes in the modeling proposed in this work, namely: Class A (Promotion by deserving), Class B (Promotion by seniority), and Class C (Military not promoted). As a result, the method presented 20% of the officers evaluated with performance corresponding to class A, 53% of the alternatives to class B, and 26.7% with performances attributed to class C. In addition, we presented a sensitivity analysis procedure through variation of the cut-off level λ, allowing decision-making on more flexible or rigorous scenarios at the discretion of the Naval High Administration. This work brings a valuable contribution to academia and society since it represents the application of an MCDM method in state of the art to contribute to solving a real problem.info:eu-repo/semantics/publishedVersio

Robust ordinal regression for value functions handling interacting criteria

International audienceWe present a new method called UTAGMS–INT for ranking a finite set of alternatives evaluated on multiple criteria. It belongs to the family of Robust Ordinal Regression (ROR) methods which build a set of preference models compatible with preference information elicited by the Decision Maker (DM). The preference model used by UTAGMS–INT is a general additive value function augmented by two types of components corresponding to ‘‘bonus’’ or ‘‘penalty’’ values for positively or negatively interacting pairs of criteria, respectively. When calculating value of a particular alternative, a bonus is added to the additive component of the value function if a given pair of criteria is in a positive synergy for performances of this alternative on the two criteria. Similarly, a penalty is subtracted from the additive component of the value function if a given pair of criteria is in a negative synergy for performances of the considered alternative on the two criteria. The preference information elicited by the DM is composed of pairwise comparisons of some reference alternatives, as well as of comparisons of some pairs of reference alternatives with respect to intensity of preference, either comprehensively or on a particular criterion. In UTAGMS–INT, ROR starts with identification of pairs of interacting criteria for given preference information by solving a mixed-integer linear program. Once the interacting pairs are validated by the DM, ROR continues calculations with the whole set of compatible value functions handling the interacting criteria, to get necessary and possible preference relations in the considered set of alternatives. A single representative value function can be calculated to attribute specific scores to alternatives. It also gives values to bonuses and penalties. UTAGMS–INT handles quite general interactions among criteria and provides an interesting alternative to the Choquet integral

Decision-Making Ontology for Information System Engineering

International audienceInformation Systems (IS) engineering (ISE) processes contain steps where decisions must be made. Moreover, the growing role of IS in organizations involves requirements for ISE such as quality, cost and time. Considering these aspects implies that the number of researches dealing with decision-making (DM) in ISE increasingly grows. As DM becomes widespread in the ISE field, it is necessary to build a representation, shared between researchers and practitioners, of DM concepts and their relations with DM problems in ISE. In this paper, we present a DM ontology which aims at formalizing DM knowledge. Its goal is to enhance DM and to support DM activities in ISE. This ontology is illustrated within the requirements engineering field

A Multi-Criteria Methodology to Support Public Administration Decision Making Concerning Sustainable Energy Action Plans

For municipalities that have joined the Covenant of Mayors promoted by the European Commission, the Sustainable Energy Action Plan (SEAP) represents a strategic tool for achieving the greenhouse gas reductions required by 2020. So far as the energy retrofit actions in their residential building stock are concerned, which in the small-to-medium municipalities are responsible for more than 60% of CO2 emissions, the scenarios for intervening are normally decided on the basis of an economic (cost/performance) analysis. This type of analysis, however, does not take into account important aspects for small and medium-sized communities such as social aspects, environmental impacts, local economic development and employment. A more comprehensive and effective tool to support the choices of public administrators is the multi-criteria analysis. This study proposes a methodology that integrates multi-criteria analysis in order to support Public Administration/Local Authorities in programming Sustainable Energy Action Plans with a more targeted approach to sustainability. The methodology, based on the ELECTRE III method, was applied to a medium-size municipality in the Lombardy region of Italy. The results obtained with this approach are discussed in this pape

Conflicting Objectives in Decisions

This book deals with quantitative approaches in making decisions when conflicting objectives are present. This problem is central to many applications of decision analysis, policy analysis, operational research, etc. in a wide range of fields, for example, business, economics, engineering, psychology, and planning. The book surveys different approaches to the same problem area and each approach is discussed in considerable detail so that the coverage of the book is both broad and deep. The problem of conflicting objectives is of paramount importance, both in planned and market economies, and this book represents a cross-cultural mixture of approaches from many countries to the same class of problem

Preference fusion and Condorcet's Paradox under uncertainty

Facing an unknown situation, a person may not be able to firmly elicit his/her preferences over different alternatives, so he/she tends to express uncertain preferences. Given a community of different persons expressing their preferences over certain alternatives under uncertainty, to get a collective representative opinion of the whole community, a preference fusion process is required. The aim of this work is to propose a preference fusion method that copes with uncertainty and escape from the Condorcet paradox. To model preferences under uncertainty, we propose to develop a model of preferences based on belief function theory that accurately describes and captures the uncertainty associated with individual or collective preferences. This work improves and extends the previous results. This work improves and extends the contribution presented in a previous work. The benefits of our contribution are twofold. On the one hand, we propose a qualitative and expressive preference modeling strategy based on belief-function theory which scales better with the number of sources. On the other hand, we propose an incremental distance-based algorithm (using Jousselme distance) for the construction of the collective preference order to avoid the Condorcet Paradox.Comment: International Conference on Information Fusion, Jul 2017, Xi'an, Chin