Distance-based consensus models for fuzzy and multiplicative 3 preference relations

This paper proposes a distance-based consensus model for fuzzy preference relations where the weights of fuzzy preference relations are automatically determined. Two indices, an individual to group consensus index (ICI) and a group consensus index (GCI), are introduced. An iterative consensus reaching algorithm is presented and the process terminates until both the ICI and GCI are controlled within predefined thresholds. The model and algorithm are then extended to handle multiplicative preference relations. Finally, two examples are illustrated and comparative analyses demonstrate the effectiveness of the proposed methods

Goal programming approaches to deriving interval fuzzy preference relations

This article investigates the consistency of interval fuzzy preference relations based on interval arithmetic, and new definitions are introduced for additive consistent, multiplicative consistent and weakly transitive interval fuzzy preference relations. Transformation functions are put forward to convert normalized interval weights into consistent interval fuzzy preference relations. By analyzing the relationship between interval weights and consistent interval fuzzy preference relations, goal-programming-based models are developed for deriving interval weights from interval fuzzy preference relations for both individual and group decision-making situations. The proposed models are illustrated by a numerical example and an international exchange doctoral student selection problem

Characterisation of the consistent completion of AHP comparison matrices using graph theory

[EN] Decision-making is frequently affected by uncertainty and/or incomplete information, which turn decision-making into a complex task. It is often the case that some of the actors involved in decision-making are not sufficiently familiar with all of the issues to make the appropriate decisions. In this paper, we are concerned about missing information. Specifically, we deal with the problem of consistently completing an analytic hierarchy process comparison matrix and make use of graph theory to characterize such a completion. The characterization includes the degree of freedom of the set of solutions and a linear manifold and, in particular, characterizes the uniqueness of the solution, a result already known in the literature, for which we provide a completely independent proof. Additionally, in the case of nonuniqueness, we reduce the problem to the solution of nonsingular linear systems. In addition to obtaining the priority vector, our investigation also focuses on building the complete pairwise comparison matrix, a crucial step in the necessary process (between synthetic consistency and personal judgement) with the experts. The performance of the obtained results is confirmed.Benítez López, J.; Carpitella, S.; Certa, A.; Izquierdo Sebastián, J. (2019). Characterisation of the consistent completion of AHP comparison matrices using graph theory. Journal of Multi-Criteria Decision Analysis. 26(1-2):3-15. https://doi.org/10.1002/mcda.1652S315261-2Benítez, J., Carrión, L., Izquierdo, J., & Pérez-García, R. (2014). Characterization of Consistent Completion of Reciprocal Comparison Matrices. Abstract and Applied Analysis, 2014, 1-12. doi:10.1155/2014/349729Benítez, J., Delgado-Galván, X., Gutiérrez, J. A., & Izquierdo, J. (2011). Balancing consistency and expert judgment in AHP. 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Interval type-2 hesitant fuzzy set method for improving the service quality of domestic airlines in Turkey

This study investigates the level of service quality of domestic airlines in Turkey travelling between Istanbul and London and compares those airline companies according to a set of predetermined criteria. A practical multi-criteria decision making approach combining hesitant and interval type 2 fuzzy sets is adopted and proposed for assessing the service quality of airline companies. The main finding of this study is that passengers care for service prioritization and personalization for a better flight experience and important differences occur in the service quality among the airline companies. Hence, handling of customer complaints, flight problems and individual attention could provide better insights for improving the service quality

A fuzzy decision tool to evaluate the sustainable performance of suppliers in an agrifood value chain

Sustainable supply chain management has received much attention from both academia and industry due to various issues such as economic stability, environment conservation, and social ethics. To improve the sustainable performance of a value chain, its members need to carefully select their suppliers in relation to their own strategy. Thus, an effective tool for sustainable supplier selection and evaluation is essential, which considers the triple bottom line (TBL) of economic, environmental and social aspects by means of criteria adapted to the situation analysed. This paper develops a fuzzy decision tool to evaluate the sustainable performance of suppliers according to TBL. Sustainability criteria are identified to take into account the real hotspots in a food value chain. The proposed model integrates triangular fuzzy numbers (TFN), AHP (Analytic Hierarchy Process) and TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) in a novel way to consider quantitative and qualitative criteria as well as objective and subjective data. This is missing in most existing research when building their fuzzy models for supplier selection, but critical in dealing with the heterogeneous data available for TBL assessment. The application in a sustainable agrifood value chain illustrates the effectiveness of the proposed tool

Uncertain Multi-Criteria Optimization Problems

Most real-world search and optimization problems naturally involve multiple criteria as objectives. Generally, symmetry, asymmetry, and anti-symmetry are basic characteristics of binary relationships used when modeling optimization problems. Moreover, the notion of symmetry has appeared in many articles about uncertainty theories that are employed in multi-criteria problems. Different solutions may produce trade-offs (conflicting scenarios) among different objectives. A better solution with respect to one objective may compromise other objectives. There are various factors that need to be considered to address the problems in multidisciplinary research, which is critical for the overall sustainability of human development and activity. In this regard, in recent decades, decision-making theory has been the subject of intense research activities due to its wide applications in different areas. The decision-making theory approach has become an important means to provide real-time solutions to uncertainty problems. Theories such as probability theory, fuzzy set theory, type-2 fuzzy set theory, rough set, and uncertainty theory, available in the existing literature, deal with such uncertainties. Nevertheless, the uncertain multi-criteria characteristics in such problems have not yet been explored in depth, and there is much left to be achieved in this direction. Hence, different mathematical models of real-life multi-criteria optimization problems can be developed in various uncertain frameworks with special emphasis on optimization problems

Managing Consistency and Consensus in Group Decision-Making with Incomplete Fuzzy Preference Relations

Group decision-making is a field of decision theory that has many strengths and benefits. It can solve and simplify the most complex and hard decision problems. In addition, it helps decision-makers know more about the problem under study and their preferences. Group decision-making is much harder and complex than individual decision-making since group members may have different preferences regarding the alternatives, making it difficult to reach a consensus. In this thesis, we deal with three interrelated problems that decision-makers encounter during the process of arriving at a final decision. Our work addresses decision-making using preference relations. The first problem deals with incomplete reciprocal preference relations, where some of the preference degrees are missing. Ideally, the group members are able to provide preferences for all the alternatives, but sometimes they might not be able to discriminate between some of the alternatives, leading to missing values. Two methods are proposed to handle this problem. The first is based on a system of equations and the second relies on goal programming to estimate the missing information. The former is suitable to complete any incomplete preference relation with at leas

Application of a multiple attribute group decision making (MAGDM) model for selecting appropriate maintenance strategy for marine and offshore machinery operations

The process of selecting appropriate maintenance strategy to enhance the operational efficiency of marine and offshore machinery under an uncertain environment is challenging due to the many criteria that need to be considered and modelled. In addition, the design of such complex machinery on-board a vessel consists of many subjective and imprecise parameters contained in different quantitative and qualitative forms. This paper proposes a strategic multi-attribute group decision-making (MAGDM) methodology for the concise and straightforward selection of an appropriate maintenance strategy. The decision support structure allows the use of multiple decision makers to incorporate and aggregate their subjective opinions transparently. In the analysis, a Technique for Order Preference by Similarity to Ideal Situation (TOPSIS) was employed to rank the maintenance strategies with respect to costs and benefits for their subsequent implementation. The purpose of using MAGDM in this paper is to aggregate and synthesise opinions of experts, thus, guiding them in decision making when they are planning to implement a cost effective maintenance investment. © 2019 Elsevier Lt

Decision-making: a laboratory-based case study in conceptual design

The engineering design process may be seen as a series of interrelated operations that are driven by decisions: each operation is carried out as the consequence of an associated decision. Hence, an effective design process relies heavily upon effective decision-making. As a consequence, supporting decision-making may be a significant means for achieving design process improvements. This thesis concentrates on how to support selection-type decision-making in conceptual engineering design. [Continues.

Customized risk assessment in military shipbuilding

This paper describes a customized risk assessment framework to be applied in military shipbuilding projects. The framework incorporates the Delphi method with visual diagrams, Bayesian Networks (BN) and the expression of expert opinions through linguistic variables. Noisy-OR and Leak Canonical models are used to determine the conditional probabilities of the BN model. The approach can easily be adapted for other shipbuilding construction projects. The visual diagrams that support the Delphi questionnaire favor the comprehensive visualization of the interdependencies between risks, causes, risks and causes, and risks and effects. The applicability of the framework is illustrated through the assessment of risk of two real military shipbuilding projects. This assessment includes a sensitivity analysis that is useful to prioritize mitigation actions. In the two cases studies, the risks with higher probability of occurrence were failures or errors in production, of the contracted, in the requirements, and in planning. The results of the sensitivity analysis showed that a set of mitigation actions directed at relatively easily controllable causes would have achieved important reductions in risk probabilities.- (undefined