876 resultados para Multicriteria Decision Analysis


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Geographic information systems give us the possibility to analyze, produce, and edit geographic information. Furthermore, these systems fall short on the analysis and support of complex spatial problems. Therefore, when a spatial problem, like land use management, requires a multi-criteria perspective, multi-criteria decision analysis is placed into spatial decision support systems. The analytic hierarchy process is one of many multi-criteria decision analysis methods that can be used to support these complex problems. Using its capabilities we try to develop a spatial decision support system, to help land use management. Land use management can undertake a broad spectrum of spatial decision problems. The developed decision support system had to accept as input, various formats and types of data, raster or vector format, and the vector could be polygon line or point type. The support system was designed to perform its analysis for the Zambezi river Valley in Mozambique, the study area. The possible solutions for the emerging problems had to cover the entire region. This required the system to process large sets of data, and constantly adjust to new problems’ needs. The developed decision support system, is able to process thousands of alternatives using the analytical hierarchy process, and produce an output suitability map for the problems faced.

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To solve a health and safety problem on a waste treatment facility, different multicriteria decision methods were used, including the PROV Exponential decision method. Four alternatives and ten attributes were considered. We found a congruent solution, validated by the different methods. The AHP and the PROV Exponential decision method led us to the same options ordering, but the last method reinforced one of the options as being the best performing one, and detached the least performing option. Also, the ELECTRE I method results led to the same ordering which allowed to point the best solution with reasonable confidence. This paper demonstrates the potential of using multicriteria decision methods to support decision making on complex problems such as risk control and accidents prevention.

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This paper presents a procedure that allows us to determine the preference structures(PS) associated to each of the different groups of actors that can be identified in a groupdecision making problem with a large number of individuals. To that end, it makesuse of the Analytic Hierarchy Process (AHP) (Saaty, 1980) as the technique to solvediscrete multicriteria decision making problems. This technique permits the resolutionof multicriteria, multienvironment and multiactor problems in which subjective aspectsand uncertainty have been incorporated into the model, constructing ratio scales correspondingto the priorities relative to the elements being compared, normalised in adistributive manner (wi = 1). On the basis of the individuals’ priorities we identifydifferent clusters for the decision makers and, for each of these, the associated preferencestructure using, to that end, tools analogous to those of Multidimensional Scaling.The resulting PS will be employed to extract knowledge for the subsequent negotiationprocesses and, should it be necessary, to determine the relative importance of thealternatives being compared using anyone of the existing procedures

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Current technology trends in medical device industry calls for fabrication of massive arrays of microfeatures such as microchannels on to nonsilicon material substrates with high accuracy, superior precision, and high throughput. Microchannels are typical features used in medical devices for medication dosing into the human body, analyzing DNA arrays or cell cultures. In this study, the capabilities of machining systems for micro-end milling have been evaluated by conducting experiments, regression modeling, and response surface methodology. In machining experiments by using micromilling, arrays of microchannels are fabricated on aluminium and titanium plates, and the feature size and accuracy (width and depth) and surface roughness are measured. Multicriteria decision making for material and process parameters selection for desired accuracy is investigated by using particle swarm optimization (PSO) method, which is an evolutionary computation method inspired by genetic algorithms (GA). Appropriate regression models are utilized within the PSO and optimum selection of micromilling parameters; microchannel feature accuracy and surface roughness are performed. An analysis for optimal micromachining parameters in decision variable space is also conducted. This study demonstrates the advantages of evolutionary computing algorithms in micromilling decision making and process optimization investigations and can be expanded to other applications

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This paper sets out to identify the initial positions of the different decision makers who intervene in a group decision making process with a reduced number of actors, and to establish possible consensus paths between these actors. As a methodological support, it employs one of the most widely-known multicriteria decision techniques, namely, the Analytic Hierarchy Process (AHP). Assuming that the judgements elicited by the decision makers follow the so-called multiplicative model (Crawford and Williams, 1985; Altuzarra et al., 1997; Laininen and Hämäläinen, 2003) with log-normal errors and unknown variance, a Bayesian approach is used in the estimation of the relative priorities of the alternatives being compared. These priorities, estimated by way of the median of the posterior distribution and normalised in a distributive manner (priorities add up to one), are a clear example of compositional data that will be used in the search for consensus between the actors involved in the resolution of the problem through the use of Multidimensional Scaling tools

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This paper presents a procedure that allows us to determine the preference structures (PS) associated to each of the different groups of actors that can be identified in a group decision making problem with a large number of individuals. To that end, it makes use of the Analytic Hierarchy Process (AHP) (Saaty, 1980) as the technique to solve discrete multicriteria decision making problems. This technique permits the resolution of multicriteria, multienvironment and multiactor problems in which subjective aspects and uncertainty have been incorporated into the model, constructing ratio scales corresponding to the priorities relative to the elements being compared, normalised in a distributive manner (wi = 1). On the basis of the individuals’ priorities we identify different clusters for the decision makers and, for each of these, the associated preference structure using, to that end, tools analogous to those of Multidimensional Scaling. The resulting PS will be employed to extract knowledge for the subsequent negotiation processes and, should it be necessary, to determine the relative importance of the alternatives being compared using anyone of the existing procedures

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El WACC o Coste Medio Ponderado de Capital es la tasa a la que se deben descontar los flujos para evaluar un proyecto o empresa. Para calcular esta tasa es necesario determinar el costo de la deuda y el costo de los recursos propios de la compañía; el costo de la deuda es la tasa actual del mercado que la empresa está pagando por su deuda, sin embargo el costo de los recursos propios podría ser difícil y más complejo de estimar ya que no existe un costo explícito. En este trabajo se presenta un panorama de las teorías propuestas a lo largo de la historia para calcular el costo de los recursos propios. Como caso particular, se estimará el costo de los recursos propios sin apalancamiento financiero de seis empresas francesas que no cotizan en bolsa y pertenecientes al sector de Servicios a la Persona (SAP). Para lograr lo anterior, se utilizará el Proceso de Análisis Jerárquico (AHP) y el Modelo de Valoración del Precio de los Activos Financieros (CAPM) con base en lo presentado por Martha Pachón (2013) en “Modelo alternativo para calcular el costo de los recursos propios”.

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Este trabajo recopila literatura académica relevante sobre estrategias de entrada y metodologías para la toma de decisión sobre la contratación de servicios de Outsourcing para el caso de empresas que planean expandirse hacia mercados extranjeros. La manera en que una empresa planifica su entrada a un mercado extranjero, y realiza la consideración y evaluación de información relevante y el diseño de la estrategia, determina el éxito o no de la misma. De otro lado, las metodologías consideradas se concentran en el nivel estratégico de la pirámide organizacional. Se parte de métodos simples para llegar a aquellos basados en la Teoría de Decisión Multicriterio, tanto individuales como híbridos. Finalmente, se presenta la Dinámica de Sistemas como herramienta valiosa en el proceso, por cuanto puede combinarse con métodos multicriterio.

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This paper presents a multicriteria decision-making model for lifespan energy efficiency assessment of intelligent buildings (IBs). The decision-making model called IBAssessor is developed using an analytic network process (ANP) method and a set of lifespan performance indicators for IBs selected by a new quantitative approach called energy-time consumption index (ETI). In order to improve the quality of decision-making, the authors of this paper make use of previous research achievements including a lifespan sustainable business model, the Asian IB Index, and a number of relevant publications. Practitioners can use the IBAssessor ANP model at different stages of an IB lifespan for either engineering or business oriented assessments. Finally, this paper presents an experimental case study to demonstrate how to use IBAssessor ANP model to solve real-world design tasks.

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Leilões são instituições seculares utilizadas nas relações comerciais entre indivíduos e organizações. Provêem maior flexibilidade aos processos de determinação de preços e alocação de bens, aumentando o espaço para negociações entre compradores e vendedores. Na Internet, têm sido empregados, de maneira crescente, em atividades de comércio eletrônico B2B e G2B, em sua maioria, através da modalidade de leilão reverso. No entanto, seu aspecto unidimensional reduz as negociações à variável preço, produzindo, muitas vezes, resultados aquém do desejado. No caso brasileiro, o Governo Federal instituiu o Portal Comprasnet, através do qual, as organizações públicas adquirem bens e serviços de fornecedores cadastrados. Dentre as modalidades de licitação disponíveis, destaca-se o Pregão Eletrônico, um mecanismo de leilão eletrônico reverso baseado no atributo preço, através do qual, fornecedores submetem lances decrescentes, na disputa por contratos do setor público. No presente trabalho, o autor propõe uma abordagem de decisão multicritério, baseada na Teoria da Utilidade Multiatributo, como uma alternativa para a adoção de leilões reversos baseados em múltiplos atributos e, consequentemente, para uma maior agregação de valor pelas organizações compradoras do setor público brasileiro.

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Objective: To To conduct a cost-effectiveness analysis of a universal childhood hepatitis A vaccination program in Brazil. Methods: An age and time-dependent dynamic model was developed to estimate the incidence of hepatitis A for 24 years. The analysis was run separately according to the pattern of regional endemicity, one for South + Southeast (low endemicity) and one for the North + Northeast + Midwest (intermediate endemicity). The decision analysis model compared universal childhood vaccination with current program of vaccinating high risk individuals. Epidemiologic and cost estimates were based on data from a nationwide seroprevalence survey of viral hepatitis, primary data collection, National Health Information Systems and literature. The analysis was conducted from both the health system and societal perspectives. Costs are expressed in 2008 Brazilian currency (Real). Results: A universal immunization program would have a significant impact on disease epidemiology in all regions, resulting in 64% reduction in the number of cases of icteric hepatitis, 59% reduction in deaths for the disease and a 62% decrease of life years lost, in a national perspective. With a vaccine price of R$16.89 (US$7.23) per dose, vaccination against hepatitis A was a cost-saving strategy in the low and intermediate endemicity regions and in Brazil as a whole from both health system and society perspective. Results were most sensitive to the frequency of icteric hepatitis, ambulatory care and vaccine costs. Conclusions: Universal childhood vaccination program against hepatitis A could be a cost-saving strategy in all regions of Brazil. These results are useful for the Brazilian government for vaccine related decisions and for monitoring population impact if the vaccine is included in the National Immunization Program. (C) 2012 Elsevier Ltd. All rights reserved.

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Different tools have been used to set up and adopt the model for the fulfillment of the objective of this research. 1. The Model The base model that has been used is the Analytical Hierarchy Process (AHP) adapted with the aim to perform a Benefit Cost Analysis. The AHP developed by Thomas Saaty is a multicriteria decision - making technique which decomposes a complex problem into a hierarchy. It is used to derive ratio scales from both discreet and continuous paired comparisons in multilevel hierarchic structures. These comparisons may be taken from actual measurements or from a fundamental scale that reflects the relative strength of preferences and feelings. 2. Tools and methods 2.1. The Expert Choice Software The software Expert Choice is a tool that allows each operator to easily implement the AHP model in every stage of the problem. 2.2. Personal Interviews to the farms For this research, the farms of the region Emilia Romagna certified EMAS have been detected. Information has been given by EMAS center in Wien. Personal interviews have been carried out to each farm in order to have a complete and realistic judgment of each criteria of the hierarchy. 2.3. Questionnaire A supporting questionnaire has also been delivered and used for the interviews . 3. Elaboration of the data After data collection, the data elaboration has taken place. The software support Expert Choice has been used . 4. Results of the Analysis The result of the figures above (vedere altro documento) gives a series of numbers which are fractions of the unit. This has to be interpreted as the relative contribution of each element to the fulfillment of the relative objective. So calculating the Benefits/costs ratio for each alternative the following will be obtained: Alternative One: Implement EMAS Benefits ratio: 0, 877 Costs ratio: 0, 815 Benfit/Cost ratio: 0,877/0,815=1,08 Alternative Two: Not Implement EMAS Benefits ratio: 0,123 Costs ration: 0,185 Benefit/Cost ratio: 0,123/0,185=0,66 As stated above, the alternative with the highest ratio will be the best solution for the organization. This means that the research carried out and the model implemented suggests that EMAS adoption in the agricultural sector is the best alternative. It has to be noted that the ratio is 1,08 which is a relatively low positive value. This shows the fragility of this conclusion and suggests a careful exam of the benefits and costs for each farm before adopting the scheme. On the other part, the result needs to be taken in consideration by the policy makers in order to enhance their intervention regarding the scheme adoption on the agricultural sector. According to the AHP elaboration of judgments we have the following main considerations on Benefits: - Legal compliance seems to be the most important benefit for the agricultural sector since its rank is 0,471 - The next two most important benefits are Improved internal organization (ranking 0,230) followed by Competitive advantage (ranking 0, 221) mostly due to the sub-element Improved image (ranking 0,743) Finally, even though Incentives are not ranked among the most important elements, the financial ones seem to have been decisive on the decision making process. According to the AHP elaboration of judgments we have the following main considerations on Costs: - External costs seem to be largely more important than the internal ones (ranking 0, 857 over 0,143) suggesting that Emas costs over consultancy and verification remain the biggest obstacle. - The implementation of the EMS is the most challenging element regarding the internal costs (ranking 0,750).

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This study investigated the effects of patient variables (physical and cognitive disability, significant others' preference and social support) on nurses' nursing home placement decision-making and explored nurses' participation in the decision-making process.^ The study was conducted in a hospital in Texas. A sample of registered nurses on units that refer patients for nursing home placement were asked to review a series of vignettes describing elderly patients that differed in terms of the study variables and indicate the extent to which they agreed with nursing home placement on a five-point Likert scale. The vignettes were judged to have good content validity by a group of five colleagues (expert consultants) and test-retest reliability based on the Pearson correlation coefficient was satisfactory (average of.75) across all vignettes.^ The study tested the following hypotheses: Nurses have more of a propensity to recommend placement when (1) patients have severe physical disabilities; (2) patients have severe cognitive disabilities; (3) it is the significant others' preference; and (4) patients have no social support nor alternative services. Other hypotheses were that (5) a nurse's characteristics and extent of participation will not have a significant effect on their placement decision; and (6) a patient's social support is the most important, single factor, and the combination of factors of severe physical and cognitive disability, significant others' preference, and no social support nor alternative services will be the most important set of predictors of a nurse's placement decision.^ Analysis of Variance (ANOVA) was used to analyze the relationships implied in the hypothesis. A series of one-way ANOVA (bivariate analyses) of the main effects supported hypotheses one-five.^ Overall, the n-way ANOVA (multivariate analyses) of the main effects confirmed that social support was the most important single factor controlling for other variables. The 4-way interaction model confirmed that the most predictive combination of patient characteristics were severe physical and cognitive disability, no social support and the significant others did not desire placement. These analyses provided an understanding of the importance of the influence of specific patient variables on nurses' recommendations regarding placement. ^