A review of fuzzy AHP methods for decision-making with subjective judgements

Analytic Hierarchy Process (AHP) is a broadly applied multi-criteria decision-making method to determine the weights of criteria and priorities of alternatives in a structured manner based on pairwise comparison. As subjective judgments during comparison might be imprecise, fuzzy sets have been combined with AHP. This is referred to as fuzzy AHP or FAHP. An increasing amount of papers are published which describe different ways to derive the weights/priorities from a fuzzy comparison matrix, but seldomly set out the relative benefits of each approach so that the choice of the approach seems arbitrary. A review of various fuzzy AHP techniques is required to guide both academic and industrial experts to choose suitable techniques for a specific practical context. This paper reviews the literature published since 2008 where fuzzy AHP is applied to decision-making problems in industry, particularly the various selection problems. The techniques are categorised by the four aspects of developing a fuzzy AHP model: (i) representation of the relative importance for pairwise comparison, (ii) aggregation of fuzzy sets for group decisions and weights/priorities, (iii) defuzzification of a fuzzy set to a crisp value for final comparison, and (iv) consistency measurement of the judgements. These techniques are discussed in terms of their underlying principles, origins, strengths and weakness. Summary tables and specification charts are provided to guide the selection of suitable techniques. Tips for building a fuzzy AHP model are also included and six open questions are posed for future work

Decision support model for the selection of asphalt wearing courses in highly trafficked roads

The suitable choice of the materials forming the wearing course of highly trafficked roads is a delicate task because of their direct interaction with vehicles. Furthermore, modern roads must be planned according to sustainable development goals, which is complex because some of these might be in conflict. Under this premise, this paper develops a multi-criteria decision support model based on the analytic hierarchy process and the technique for order of preference by similarity to ideal solution to facilitate the selection of wearing courses in European countries. Variables were modelled using either fuzzy logic or Monte Carlo methods, depending on their nature. The views of a panel of experts on the problem were collected and processed using the generalized reduced gradient algorithm and a distance-based aggregation approach. The results showed a clear preponderance by stone mastic asphalt over the remaining alternatives in different scenarios evaluated through sensitivity analysis. The research leading to these results was framed in the European FP7 Project DURABROADS (No. 605404).The research leading to these results has received funding from the European Union Seventh Framework Programme (FP7/2007–2013) under Grant Agreement No. 605404

Inconsistency and non-additive Choquet integration in the Analytic Hierarchy Process

We propose to extend the aggregation scheme of Saaty’s AHP, from the stan- dard weighted averaging to the more general Choquet integration. In our model, a measure of inconsistency between criteria is derived from the main pairwise comparison matrix and it is used to construct a non-additive capacity, whose associated Choquet integral reduces to the standard weighted mean in the con- sistency case. In the general inconsistency case, however, the new aggregation scheme based on Choquet integration tends to attenuate (resp. emphasize) the priority values of the criteria with higher (resp. lower) average inconsistency with the remaining criteria.Aggregation Functions, Multiple Criteria Analysis, AHP, Inconsintency, non-additive measures, Choquet integral, and Shapley values.

Intelligent protocol adaptation for enhanced medical e-collaboration

Copyright @ 2003 AAAIDistributed multimedia e-health applications have a set specific requirements which must be taken into account effective use is to be made of the limited resources provided by public telecommunication networks. Moreover, there an architectural gap between the provision of network-level Quality of Service (QoS) and user requirements of e-health applications. In this paper, we address the problem bridging this gap from a multi-attribute decision-making perspective in the context of a remote collaborative environment for back pain treatment. We propose intelligent mechanism that integrates user- related requirements with the more technical characterisation Quality of Service. We show how our framework is capable of suggesting appropriately tailored transmission protocols, by incorporating user requirements in the remote delivery e-health solutions

An evaluation methodology for ergonomic design of electronic consumer products based on fuzzy axiomatic design

This article is posted with permission of OCP Science imprint. Copyright @ 2008 Old City Publishing Group.The development life cycle of software and electronic products has been shortened by the growth of rapid prototyping techniques. The evaluation of electronic consumer products should consider hardware and software as well as the ergonomic usability, emotional appeal and aesthetic integrity of the design. This research follows a systematic approach to develop an evaluation methodology for electronic mobile products on ergonomic design. The proposed methodology is based on fuzzy multi attribute decision making and fuzzy axiomatic design realized in three steps; determination of ergonomic attributes for electronic consumer products, determination of a representative set of alternatives, and selection of the best alternative in terms of ergonomic design by utilizing fuzzy axiomatic design. A case study is also provided to support the proposed methodology

A GIS-based offshore wind site selection model using fuzzy multi-criteria decision-making with application to the case of the Gulf of Maine

In the last decades, a considerable number of studies have been conducted to find the optimal locations for renewable energy facilities. The reviewed literature demonstrates how the combination of spatial representation computer tools, such as geographic information systems (GIS), with multi-criteria decision making (MCDM) methodologies, has successfully solved the problem of identifying optimal locations. Furthermore, since the appearance of fuzzy logic, the combination approaches have extended to the field of fuzzy sets to consider the imprecision and vagueness that some criteria may involve. In this paper, we propose a comparative analysis among fuzzy versions of MCDM methodologies, including GIS technologies, for the optimal site selection of offshore wind power plants. With this aim, we combined a classical pair-wise comparison method (AHP) with two distance-based approaches (TOPSIS and VIKOR), applying GIS software and comparing the two most extended fuzzy membership functions: triangular and linear. As a case study, this optimal location problem was applied to offshore wind site selection in the Gulf of Maine (USA). Initially, 56 alternatives for potential locations were identified from 22,331 km study area. After applying the AHP methodology, the weights of the criteria were obtained, turning out to be the wind speed and bathymetry the most important criteria. The results demonstrate the robustness of the fuzzy TOPSIS methodology against potential variations in the criteria weights, since the best alternatives (optimal locations) and almost 90% of the 25 top–ranked alternatives were matching. Likewise, the rankings of alternatives illustrate that the use of triangular or linear fuzzy membership functions does not cause significant differences after applying the fuzzy VIKOR methodology and ArcGIS software. In fact, the most appropriate alternative is the same for both cases, and there is only an exchange of positions among the top–ranked alternatives. The proposed solutions can be applied to other locations and both onshore and offshore installations.2021-2