SURVEY DESIGN USING INDIVIDUAL NUMERICAL SCALES IN THE FRAMEWORK OF ANALYTIC HIERARCHY PROCESSES

This paper discusses the adequacy of a generalization of Saaty’s 1-9 scale proposed by Liang at all (2008) in the attempt to identify individual scales. Several surveys in completely different areas were conducted on different topics. Comparisons among the consistency index-as a measure of a “good answer” and the previously mentioned scale reveal a non monotonic correspondence among those two criterions. Also, the individual scale considered – which is in itself a generalization of other similar scales for measuring individual responses – is not uniquely determined for a single respondent and is very often contradictory. Yet, the potential benefits in determining individual scales of measurement are enormous and maybe the most important one is getting rid of the myth of the good appliance of the “law of large numbers” in social sciences.Analytic Hierarchy Processes, knowledge sharing, mapping, numerical scale, simulated annealing, verbal responses.

Influence of aggregation and measurement scale on ranking a compromise alternative in AHP

Analytic Hierarchy Process (AHP) is one of the most popular multi-attribute decision aid methods. However, within AHP, there are several competing preference measurement scales and aggregation techniques. In this paper, we compare these possibilities using a decision problem with an inherent trade-off between two criteria. A decision-maker has to choose among three alternatives: two extremes and one compromise. Six different measurement scales described previously in the literature and the new proposed logarithmic scale are considered for applying the additive and the multiplicative aggregation techniques. The results are compared with the standard consumer choice theory. We find that with the geometric and power scales a compromise is never selected when aggregation is additive and rarely when aggregation is multiplicative, while the logarithmic scale used with the multiplicative aggregation most often selects the compromise that is desirable by consumer choice theory.AHP, Multi-criteria Decision analysis

Towards secure judgments aggregation in AHP

In the decision making methods the common assumption is the honesty and professionalism of experts. However, this is not the case when one or more experts in the group decision making framework, such as the group analytic hierarchy process (GAHP), try to manipulate results in their favor. The aim of this paper is to introduce two heuristics in the GAHP setting allowing to detect the manipulators and minimize their effect on the group consensus by diminishing their weights. The first heuristic is based on the assumption that manipulators will provide judgments which can be considered outliers with respect to judgments of the rest of the experts in the group. Second heuristic assumes that dishonest judgments are less consistent than average consistency of the group. Both approaches are illustrated with numerical examples and simulations.Comment: 32 page

Current practice and challenges towards handling uncertainty for effective outcomes in maintenance

The combination of viable heuristic attributes with statistical measurements presents significant challenges in industrial maintenance for complex assets under through-life service contracts. Techniques to obtain and process heuristic attributes raise numerous uncertainties which often go undefined and unmitigated. A holistic view of these uncertainties may improve decision-making capabilities and reduce maintenance costs and turnaround time. It is therefore necessary to identify and rank factors that influence uncertainties originating from challenges in the above context. This, along with an identification of who contributes to such challenges and current practice to handle them, sets the focus for this study. The influence of 32 categorised factors on uncertainty is assessed through a questionnaire completed by nine experienced maintenance managers from a leading defence company. The pedigree approach is applied to score validity of respondents’ answers according to their experience and job role to normalise scores. Results are discussed in interviews with respondents along with current practice in and ways to improve uncertainty assessment. Scores are weighted through the Analytical Hierarchy Process (AHP) in order to identify the most influential factors on uncertainty in maintenance. The analysis revealed that these include: intellectual property rights (IPR), maintainer performance, quality of information, resistance to change, stakeholder communication and technology integration. These are verified with 40 practitioners from various industrial backgrounds. From the interviews, it is deemed that a holistic view of heuristic and statistical attributes ultimately allows for more accomplished decision-making but requires trade-offs between quality and cost over the asset’s life cycle

An Analytic Hierarchy Process for The Evaluation of Transport Policies to Reduce Climate Change Impacts

Transport is the sector with the fastest growth of greenhouse gases emissions, both in developed and in developing countries, leading to adverse climate change impacts. As the experts disagree on the occurrence of these impacts, by applying the analytic hierarchy process (AHP), we have faced the question on how to form transport policies when the experts have different opinions and beliefs. The opinions of experts have been investigated by a means of a survey questionnaire. The results show that tax schemes aiming at promoting environmental-friendly transport mode are the best policy. This incentives public and environmental-friendly transport modes, such as car sharing and car pooling.Analytic Hierarchy Process, Transport Policies, Climate Change

Improving the process of analysis and comparison of results in dependability benchmarks for computer systems

Tesis por compendioLos dependability benchmarks (o benchmarks de confiabilidad en español), están diseñados para evaluar, mediante la categorización cuantitativa de atributos de confiabilidad y prestaciones, el comportamiento de sistemas en presencia de fallos. En este tipo de benchmarks, donde los sistemas se evalúan en presencia de perturbaciones, no ser capaces de elegir el sistema que mejor se adapta a nuestras necesidades puede, en ocasiones, conllevar graves consecuencias (económicas, de reputación, o incluso de pérdida de vidas). Por esa razón, estos benchmarks deben cumplir ciertas propiedades, como son la no-intrusión, la representatividad, la repetibilidad o la reproducibilidad, que garantizan la robustez y precisión de sus procesos. Sin embargo, a pesar de la importancia que tiene la comparación de sistemas o componentes, existe un problema en el ámbito del dependability benchmarking relacionado con el análisis y la comparación de resultados. Mientras que el principal foco de investigación se ha centrado en el desarrollo y la mejora de procesos para obtener medidas en presencia de fallos, los aspectos relacionados con el análisis y la comparación de resultados quedaron mayormente desatendidos. Esto ha dado lugar a diversos trabajos en este ámbito donde el proceso de análisis y la comparación de resultados entre sistemas se realiza de forma ambigua, mediante argumentación, o ni siquiera queda reflejado. Bajo estas circunstancias, a los usuarios de los benchmarks se les presenta una dificultad a la hora de utilizar estos benchmarks y comparar sus resultados con los obtenidos por otros usuarios. Por tanto, extender la aplicación de los benchmarks de confiabilidad y realizar la explotación cruzada de resultados es una tarea actualmente poco viable. Esta tesis se ha centrado en el desarrollo de una metodología para dar soporte a los desarrolladores y usuarios de benchmarks de confiabilidad a la hora de afrontar los problemas existentes en el análisis y comparación de resultados. Diseñada para asegurar el cumplimiento de las propiedades de estos benchmarks, la metodología integra el proceso de análisis de resultados en el flujo procedimental de los benchmarks de confiabilidad. Inspirada en procedimientos propios del ámbito de la investigación operativa, esta metodología proporciona a los evaluadores los medios necesarios para hacer su proceso de análisis explícito, y más representativo para el contexto dado. Los resultados obtenidos de aplicar esta metodología en varios casos de estudio de distintos dominios de aplicación, mostrará las contribuciones de este trabajo a mejorar el proceso de análisis y comparación de resultados en procesos de evaluación de la confiabilidad para sistemas basados en computador.Dependability benchmarks are designed to assess, by quantifying through quantitative performance and dependability attributes, the behavior of systems in presence of faults. In this type of benchmarks, where systems are assessed in presence of perturbations, not being able to select the most suitable system may have serious implications (economical, reputation or even lost of lives). For that reason, dependability benchmarks are expected to meet certain properties, such as non-intrusiveness, representativeness, repeatability or reproducibility, that guarantee the robustness and accuracy of their process. However, despite the importance that comparing systems or components has, there is a problem present in the field of dependability benchmarking regarding the analysis and comparison of results. While the main focus in this field of research has been on developing and improving experimental procedures to obtain the required measures in presence of faults, the processes involving the analysis and comparison of results were mostly unattended. This has caused many works in this field to analyze and compare results of different systems in an ambiguous way, as the process followed in the analysis is based on argumentation, or not even present. Hence, under these circumstances, benchmark users will have it difficult to use these benchmarks and compare their results with those from others. Therefore extending the application of these dependability benchmarks and perform cross-exploitation of results among works is not likely to happen. This thesis has focused on developing a methodology to assist dependability benchmark performers to tackle the problems present in the analysis and comparison of results of dependability benchmarks. Designed to guarantee the fulfillment of dependability benchmark's properties, this methodology seamlessly integrates the process of analysis of results within the procedural flow of a dependability benchmark. Inspired on procedures taken from the field of operational research, this methodology provides evaluators with the means not only to make their process of analysis explicit to anyone, but also more representative for the context being. The results obtained from the application of this methodology to several case studies in different domains, will show the actual contributions of this work to improving the process of analysis and comparison of results in dependability benchmarking for computer systems.Els dependability benchmarks (o benchmarks de confiabilitat, en valencià), són dissenyats per avaluar, mitjançant la categorització quantitativa d'atributs de confiabilitat i prestacions, el comportament de sistemes en presència de fallades. En aquest tipus de benchmarks, on els sistemes són avaluats en presència de pertorbacions, el no ser capaços de triar el sistema que millor s'adapta a les nostres necessitats pot tenir, de vegades, greus conseqüències (econòmiques, de reputació, o fins i tot pèrdua de vides). Per aquesta raó, aquests benchmarks han de complir certes propietats, com són la no-intrusió, la representativitat, la repetibilitat o la reproductibilitat, que garanteixen la robustesa i precisió dels seus processos. Així i tot, malgrat la importància que té la comparació de sistemes o components, existeix un problema a l'àmbit del dependability benchmarking relacionat amb l'anàlisi i la comparació de resultats. Mentre que el principal focus d'investigació s'ha centrat en el desenvolupament i la millora de processos per a obtenir mesures en presència de fallades, aquells aspectes relacionats amb l'anàlisi i la comparació de resultats es van desatendre majoritàriament. Açò ha donat lloc a diversos treballs en aquest àmbit on els processos d'anàlisi i comparació es realitzen de forma ambigua, mitjançant argumentació, o ni tan sols queden reflectits. Sota aquestes circumstàncies, als usuaris dels benchmarks se'ls presenta una dificultat a l'hora d'utilitzar aquests benchmarks i comparar els seus resultats amb els obtinguts per altres usuaris. Per tant, estendre l'aplicació dels benchmarks de confiabilitat i realitzar l'explotació creuada de resultats és una tasca actualment poc viable. Aquesta tesi s'ha centrat en el desenvolupament d'una metodologia per a donar suport als desenvolupadors i usuaris de benchmarks de confiabilitat a l'hora d'afrontar els problemes existents a l'anàlisi i comparació de resultats. Dissenyada per a assegurar el compliment de les propietats d'aquests benchmarks, la metodologia integra el procés d'anàlisi de resultats en el flux procedimental dels benchmarks de confiabilitat. Inspirada en procediments propis de l'àmbit de la investigació operativa, aquesta metodologia proporciona als avaluadors els mitjans necessaris per a fer el seu procés d'anàlisi explícit, i més representatiu per al context donat. Els resultats obtinguts d'aplicar aquesta metodologia en diversos casos d'estudi de distints dominis d'aplicació, mostrarà les contribucions d'aquest treball a millorar el procés d'anàlisi i comparació de resultats en processos d'avaluació de la confiabilitat per a sistemes basats en computador.Martínez Raga, M. (2018). Improving the process of analysis and comparison of results in dependability benchmarks for computer systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/111945TESISCompendi

Unified Bayesian Frameworks for Multi-criteria Decision-making Problems

This paper presents Bayesian frameworks for different tasks within multi-criteria decision-making (MCDM) based on a probabilistic interpretation of the MCDM methods and problems. Owing to the flexibility of Bayesian models, the proposed frameworks can address several long-standing and fundamental challenges in MCDM, including group decision-making problems and criteria correlation, in a statistically elegant manner. Also, the models can accommodate different forms of uncertainty in the preferences of the decision makers (DMs), such as normal and triangular distributions as well as interval preferences. Further, a probabilistic mixture model is developed that can group the DMs into several exhaustive classes. A probabilistic ranking scheme is also designed for both criteria and alternatives, where it identifies the extent to which one criterion/alternative is more important than another based on the DM(s) preferences. The experiments validate the outcome of the proposed frameworks on several numerical examples and highlight its salient features compared to other methods