A multi-step goal programming approach for group decision making with incomplete interval additive reciprocal comparison matrices

This article presents a goal programming framework to solve group decision making problems where decision-makers’ judgments are provided as incomplete interval additive reciprocal comparison matrices (IARCMs). New properties of multiplicative consistent IARCMs are put forward and used to define consistent incomplete IARCMs. A two-step goal programming method is developed to estimate missing values for an incomplete IARCM. The first step minimizes the inconsistency of the completed IARCMs and controls uncertainty ratios of the estimated judgments within an acceptable threshold, and the second step finds the most appropriate estimated missing values among the optimal solutions obtained from the previous step. A weighted geometric mean approach is proposed to aggregate individual IARCMs into a group IARCM by employing the lower bounds of the interval additive reciprocal judgments. A two-step procedure consisting of two goal programming models is established to derive interval weights from the group IARCM. The first model is devised to minimize the absolute difference between the logarithm of the group preference and that of the constructed multiplicative consistent judgment. The second model is developed to generate an interval-valued priority vector by maximizing the uncertainty ratio of the constructed consistent IARCM and incorporating the optimal objective value of the first model as a constraint. Two numerical examples are furnished to demonstrate validity and applicability of the proposed approach

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

The Analytic Hierarchy Process: A Tutorial for Use in Prioritizing Forest Road Investments to Minimize Environmental Effects

The prioritization of road maintenance projects is an important forest engineering task due to limited budgets and competing investment needs. Large investments are made each year to maintain and upgrade forest road networks to meet economic and environmental goals. Many models and guidelines are available for single-criteria analysis of forest roads, however we have found no method for multi-criteria analysis. Additionally, even single criteria approaches often rely on expert judgment to inform models of user preferences and priorities. These preferences are used to make tradeoffs between alternatives that contain data that are physical and biological, quantitative and qualitative, and measured on many different scales. The Analytic Hierarchy Process (AHP) has the potential to provide a consistent approach to the ranking of forest road investments based on multiple criteria. AHP was specifically developed to provide a consistent, quantifiable approach to problems involving multi-criteria analysis, but it has not been applied to road management. AHP is composed of four steps: the hierarchical decomposition of a problem into a goal, objectives, and sub-objectives; the use of a pairwise comparison technique to determine user preferences; the scaling of attribute values for each of the alternatives; and the ranking of alternatives. The road investment problem differs from traditional AHP applications in that potentially thousands of alternatives are compared at one time. We discuss the AHP methodology including the foundations, assumptions, and potential for use in prioritizing forest road investments to meet economic and environmental goals, drawing from an example from the Oregon State University College Forests

A multi-attribute decision making procedure using fuzzy numbers and hybrid aggregators

The classical Analytical Hierarchy Process (AHP) has two limitations. Firstly, it disregards the aspect of uncertainty that usually embedded in the data or information expressed by human. Secondly, it ignores the aspect of interdependencies among attributes during aggregation. The application of fuzzy numbers aids in confronting the former issue whereas, the usage of Choquet Integral operator helps in dealing with the later issue. However, the application of fuzzy numbers into multi-attribute decision making (MADM) demands some additional steps and inputs from decision maker(s). Similarly, identification of monotone measure weights prior to employing Choquet Integral requires huge number of computational steps and amount of inputs from decision makers, especially with the increasing number of attributes. Therefore, this research proposed a MADM procedure which able to reduce the number of computational steps and amount of information required from the decision makers when dealing with these two aspects simultaneously. To attain primary goal of this research, five phases were executed. First, the concept of fuzzy set theory and its application in AHP were investigated. Second, an analysis on the aggregation operators was conducted. Third, the investigation was narrowed on Choquet Integral and its associate monotone measure. Subsequently, the proposed procedure was developed with the convergence of five major components namely Factor Analysis, Fuzzy-Linguistic Estimator, Choquet Integral, Mikhailov‘s Fuzzy AHP, and Simple Weighted Average. Finally, the feasibility of the proposed procedure was verified by solving a real MADM problem where the image of three stores located in Sabak Bernam, Selangor, Malaysia was analysed from the homemakers‘ perspective. This research has a potential in motivating more decision makers to simultaneously include uncertainties in human‘s data and interdependencies among attributes when solving any MADM problems

Is technical efficiency affected by farmers’ preference for mitigation and adaptation actions against climate change? A case study in northwest Mexico

Climate change has adverse effects on agriculture, decreasing crop quality and productivity. This makes it necessary to implement adaptation and mitigation strategies that contribute to the maintenance of technical efficiency (TE). This study analyzed the relationship of TE with farmers’ mitigation and adaptation action preferences, their risk and environmental attitudes, and their perception of climate change. Through the stochastic frontier method, TE levels were estimated for 370 farmers in Northwest Mexico. The results showed the average efficiency levels (57%) for three identified groups of farmers: High TE (15% of farmers), average TE (72%), and low TE (13%). Our results showed a relationship between two of the preferred adaptation actions against climate change estimated using the analytical hierarchy process (AHP) method. The most efficient farmers preferred “change crops,” while less efficient farmers preferred “invest in irrigation infrastructure.” The anthropocentric environmental attitude inferred from the New Ecological Paradigm (NEP) scale was related to the level of TE. Efficient farmers were those with an anthropocentric environmental attitude, compared to less efficient farmers, who exhibited an ecocentric attitude. The climate change issues were more perceived by moderately efficient farmers. These findings set out a roadmap for policy-makers to face climate change at the regional levelPeer ReviewedPostprint (published version

GIS based modelling for fuel reduction using controlled burn in Australia : case study : Logan City, Queensland

Bushfire problem is a long-lasting problem which is a big threat and environmental problem in Australia. Planning to control bushfire is very important for Australian Environment. One of the most effective methods to fight bushfire disasters is planning for controlled burns in order to reduce the risk of unwanted bushfire events. Controlled burns management and planning has been always considered as important by town planners. In this study the aim is to produce a tool for prioritizing burn blocks based on diffract criteria in order to help planners have a sound scientific basis for choosing the most important blocks to have controlled burn on. In this study the following research tasks have been considered 1. Investigate criteria related to prescribed burn management and their usability to design a model for analysing long term geospatial suitability of bushfire prescribed burns. 2. Finding out suitable model for scoring blocks designated as fuel reduction bushfire prescribed burns blocks in long term 3. Testing model in a pilot area Several criteria for building up a multi-criteria analysis with GIS model were studied and the corresponding importance weight for them were debated. Research methodology used in this section was investigating literature and methods for determining weights and possibly, using experts’ ideas by interviews or small surveys or running focus groups in a stakeholder organization to find out the most relevant and the most important criteria. Finally eleven most important criteria were chosen and compared to each other by interviewees to find out their importance weight. The model developed considers all the criteria which is usable to plan and prioritize burn blocks selected in the criteria analysis phase. This model works as a basis for having a sound and robust decision on which blocks are most suitable to be burnt in long term point of view. GIS database used in this model were acquired from the pilot area’s relevant authorities. Model was developed based on the ESRI’s ArcGIS analysis tools as well as ArcGIS Spatial Analyst extension. In this model Analytical Hierarchical Process Methodology was used for combining criteria importance and develop a unified value-based solution to the study’s Multi Criteria Analysis problem based on two main themes of ‘Implementation’ and ‘Safety’. Model was tested on Logan City Area in south of Queensland, Australia. The case study is an administration area within Australia that all the criteria data has been prepared and acquired from. Results: As combining the final results by overlaying can cause some bias as some blocks show a good match for safety theme but not a good match for implementation and vice versa, two main themes results were combined using an optimization methodology based on probabilistic principles for generating final prioritized blocks. The usability test of the result generated by this model was done by Logan City Council managers and Parks Department bushfire experts. The suitability of the blocks was very close to what experts had in their minds and this model results were validated completely satisfactory by them. All of the blocks ranked by the model were according to what they had a practical perception from the field visit and field knowledge. In overall and in general, the tool created by this study, will help decision makers has a good basis for deciding about long term priorities to plan for controlled burn activities. Decision makers could use this model to have a long term outlook for the budget and resources needed to be allocated to fuel reduction controlled burn practices. This will facilitate short term planning as well.Bushfire problem is a long-lasting problem which is a big threat and environmental problem in Australia. Planning to control bushfire is very important for Australian Environment. One of the most effective methods to fight bushfire disasters is planning for controlled burns in order to reduce the risk of unwanted bushfire events. In controlled burn, some patches or blocks which are risky to cause threat to environment and humans are selected and burned deliberately under a very safe and controlled condition. This way it is ensured that in real situations the ready-to-burn barks and tree canopy or simply ‘fuel load’ are eliminated from the area. This research aims to investigate different approaches to build up spatial model to aid decision makers have a rational justifications for planning controlled burns in long term. This includes finding out suitable model for scoring blocks designated as bushfire prescribed burns blocks. The target of this research is to investigate suitability criteria related to prescribed burn management and use them to design a model for analysing spatial suitability for bushfire prescribed burns. In the process of this research, first it is tried to find out how prescribed burn programs work, what characteristics a burn plan has and how different criteria may contribute in forming suitability for performing a prescribed burn. Then a model has been developed for this purpose. The model output is the prioritized blocks based on two main themes of ‘Safety’ and ‘Implementation’. A combination of these two themes has been used in order to generate prioritized blocks. In this output the higher is the rank of a block it means that it has higher priority to be burn first in long term planning. The model was tested in Logan City area in South East Queensland Australia. Finally the outcome showed a good agreement between planners suitability choice which was based on field visits and the prioritized blocks generated by model. This agreement was investigated gathering different decision makers’ opinions regarding different blocks and comparing it with the actual model outcome. In overall and in general, the tool created by this study, will help decision makers has a good basis for deciding about long term priorities to plan for controlled burn activities. Decision makers could use this model to have a long term outlook for the budget and resources needed to be allocated to fuel reduction controlled burn practices. This will facilitate short term planning as well

Improved Methods for Network Screening and Countermeasure Selection for Highway Improvements

Network screening and countermeasure selection are two crucial steps in the highway improvement process. In network screening, potential improvement locations are ranked and prioritized based on a specific method with a set of criteria. The most common practice by transportation agencies has been to use a simple scoring method, which, in general, weighs and scores each criterion and then ranks the locations based on their relative overall scoring. The method does not deal well with criteria that are qualitative in nature, nor does it account for the impacts of correlation among the criteria. The introduction of Analytic Hierarchy Process (AHP) provides agencies with a method to include both quantitative and qualitative criteria. However, it does not address the issue on correlation. This dissertation explores the use of both Analytic Network Process (ANP) and Fuzzy Analytic Network Process (FANP) for their potential capabilities to address both issues. Using urban four-lane divided highways in Florida for bicycle safety improvements, both ANP and FANP were shown to provide more reasonable rankings than AHP, with FANP providing the best results among the methods. After the locations are ranked and prioritized for improvements, the next step is to evaluate the potential countermeasures for improvements at the selected top-ranked locations. In this step, the standard practice has been to use Crash Modification Factors (CMFs) to quantify the potential impacts from implementing specific countermeasures. In this research, CMFs for bicycle crashes on urban facilities in Florida were developed using the Generalized Linear Model approach with a Zero-Inflated Negative Binomial (ZINB) distribution. The CMFs were tested for their spatial and temporal transferability and the results show only limited transferability both spatially and temporally. The CMFs show that, in general, wider lanes, lower speed limits, and presence of vegetation in the median reduce bicycle crashes, while presence of sidewalk and sidewalk barrier increase bicycle crashes. The research further considered bicycle exposure using the bicycle activity data from the Strava smartphone application. It was found that increased bicycle activity reduces bicycle crash probabilities on segments but increases bicycle crash probabilities at signalized intersections. Also, presence of bus stops and use of permissive signal phasing at intersections were found to increase bicycle crash probabilities

Avaliações hidrológicas, hidráulicas e multicriteriais de susceptibilidade às inundações em áreas urbanas costeiras : estudo de caso da bacia do Rio Juqueriquerê no Brasil

Orientadores: Antonio Carlos Zuffo, Monzur Alam ImteazTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Civil, Arquitetura e Urbanismo e Swinburne University of Technology (Australia)Resumo: O desenvolvimento significativo de Caraguatatuba é traduzido pela sua potencialidade ao turismo, exploração de gás, proximidade do Porto de São Sebastião e ampliação do complexo viário da Tamoios, particularmente na Bacia do Rio Juqueriquerê, que é a maior planície não urbanizada do litoral norte de São Paulo, Brasil. A área é constituída por baixas declividades e lençóis freáticos rasos, cercada pelas altas escarpas da Serra do Mar. Além disso, é afetada por chuvas orográficas e variação de marés, contribuindo para a ocorrência natural de inundações. Apesar da área à jusante ser densamente urbanizada, a bacia não é propriamente monitorada, tornando a previsão de futuros cenários com a tradicional modelagem hidrológica muito desafiadora, devido à falta de dados representativos. No presente estudo, a análise multicriterial para tomada de decisão (MCDA) foi utilizada para determinar os critérios mais impactantes na susceptibilidade às inundações do local. O cenário futuro foi baseado no uso e cobertura da terra proposto pelo Plano Diretor de Caraguatatuba. A pesquisa com especialistas usando o método Delphi e o Processo de Análise Hierárquica (AHP) foram associados para a atribuição e comparação por pares dos seguintes critérios: elevação, densidade de drenagem, chuva, declividade e Curva Número (CN), do Serviço de Conservação do Solo (SCS) dos Estados Unidos. A bacia foi discretizada em 11 sub-bacias, e vários métodos estatísticos e empíricos foram empregados para a parametrização do modelo multicriterial. Após a definição dos critérios e tratamento estatístico dos julgamentos de todos os especialistas, uma faixa limitada de pesos foi gerada, variando de 8,36 a 8,88, a qual foi efetivamente convertida para uma ampla faixa de valores de prioridade pelo uso de uma abordagem extendida do método AHP. A escala de julgamento da raiz quadrada aplicada no estudo gerou resultados de boa qualidade, onde a taxa de consistência foi de 0,0218 e o índice de consistência foi de 0,0244. Além disso, a análise de sensibilidade revelou a coerência do vetor peso, por meio da variação do critério de elevação (+10 % e -5%), afetando os pesos mas não a hierarquia. Posteriormente, todos os critérios foram implementados no sistema de informações geográficas (SIG). Foi realizada uma discussão minuciosa sobre a aquisição da variável CN, levando em consideração os tipos de solo brasileiros e as condições de saturação locais. As limitações do método SCS-CN foram destacadas, especialmente no que se refere à sua aplicação em bacias não monitoradas, quando não é possível calibrar ou validar o modelo. A estimativa e a calibração dos coeficientes de rugosidade de Manning nos principais cursos d'água também foram desenvolvidas no estudo, com base nos dados observados e medidos em trabalhos de campo. Os desvios médios absolutos entre os valores de Manning variaram de 0,004 a 0,008, mostrando que a metodologia proposta pode ser aplicada em quaisquer áreas de estudo, tanto para calibrar quanto para atualizar os coeficientes de rugosidade de Manning em diferentes períodos. A distribuição da função gamma foi utilizada para o cálculo das chuvas de projeto, que posteriormente foram utilizadas para a análise de correlação entre chuvas anuais e diárias. O Sistema de Análise Fluvial do Centro de Engenharia Hidrológica em 2 dimensões (HEC-RAS 2D) e o Sistema de Modelagem Hidrológica (HEC-HMS) foram utilizados para a calibração do parâmetro CN e para a validação do modelo. Os limites de inundação gerados no processo de vadidação (pelo modelo HEC-RAS 2D) foram muito similares aos gerados pela abordagem MCDA, correspondendo a 93,92 % e 96,31 %, respectivamente. Os métodos de interpolação foram essenciais para a distribuição temporal e espacial dos dados meteorológicos no modelo de precipitação-vazão usados para validação, e também no modelo MCDA implementado no SIG. A determinação final da probabilidade de susceptibilidade às inundações nas planícies estudadas foi baseada na soma ponderada espacial dos critérios atribuídos previamente. Por fim, os mapas de susceptibilidade às inundações foram gerados para os diferentes cenários. As simulações de diferentes padrões de chuva mostraram que este critério influenciou fortemente na probabilidade de suscetibilidade às inundações. Para a simulação de maiores elevações e chuvas máximas, o índice de susceptibilidade às inundações foi 4 (do total de 5). A maior contribuição do estudo foi na aquisição de parâmetros confiáveis por meio das técnicas propostas, que também podem ser utilizadas em outras áreas, principalmente onde os dados são escassos e há complexas limitações físicas envolvidas, visando o desenvolvimento urbano sustentável da regiãoAbstract: The significant development of Caraguatatuba Municipality is translated by its tourism potentiality, gas exploration, proximity to the Port of Sao Sebastiao and extension of the Tamoios Highway complex, particularly in the Juqueriquere River Basin, which is the major non-urbanised plains of the northern coastline of Sao Paulo, Brazil. The area is comprised of low slopes and shallow water tables, surrounded by the high elevations of the Serra do Mar mountains. Additionally, It is affected by orographic rainfalls and tide variation, contributing to the natural occurrence of floods. Even though the downstream area is densely urbanised, the watershed is not properly gauged, making it a challenging task for the prediction of future scenarios with the traditional hydrological modelling approach, due to the lack of representative data. In the current study, multicriteria decision analysis (MCDA) were used to determine the mostly impacting criteria to the local flood susceptibility. The future scenario was based on the land use and land cover proposed by the City Master Plan of Caraguatatuba. The expert-based survey using the Delphi method and the analytical hierarchical process (AHP) were associated with the attribution and pairwise comparison of the following criteria: elevation, density drainage, rainfall, slope and curve number (CN), from the US Soil Conservation Service (SCS). The watershed was discretised in 11 sub-basins, and several statistical and empirical methods were employed for the parameterisation of the multicriteria model. After the definition of the criteria and the statistical treatment of the judgements of all experts, a limited range of weights was derived, varying from 8.36 to 8.88, which was effectively converted to a larger ratio of priority values by the use of an extended approach of the AHP methodology. The root square judgement scale applied in the study generated good-quality results, where the consistency ratio was 0.0218 and the consistency index was 0.0244. Besides, the sensitivity analysis revealed the coherence of the weight vector, by the variation of the elevation criterion (+10 % and -5%), affecting the weights but not the hierarchy. Further, all the criteria were implemented in the geographical information system (GIS). There was a thorough discussion regarding the acquisition of the CN variable, taking into consideration the Brazilian soil types and the local saturated conditions. The constraints of the SCS-CN method were highlighted, especially regarding its application in ungauged basins, where it is not possible to calibrate or validate the model. The estimation and calibration of the Manning's roughness coefficients of the main watercourses were also developed in the study, based on the observed and measured data in field campaigns. The mean absolute deviations between the estimated and the calibrated Manning's values varied from 0.004 and 0.008, showing that the proposed methodology might be applied in any study areas, both to calibrate and to update the Manning's roughness coefficients in different periods. The gamma-function distribution was carried out to calculate the design rainfalls, which were later used for the correlation analysis of the annual and the daily rainfalls. The Hydrologic Engineering Center's River Analysis System 2D (HEC-RAS 2D) and the Hydrologic Modelling System (HEC-HMS) were used for the calibration of the CN variable and for the model validation. The inundation boundaries derived in the validation process (by the HEC-RAS 2D model) were very similar to the ones achieved by the MCDA approach, corresponding to 93.92 % and 96.31 %, respectively. The interpolation methods were essential for the spatial and temporal distribution of the meteorological data in the rainfall-runoff model used for validation, and also in the GIS-based MCDA model. The final determination of the likelihood of flood susceptibility in the studied plains was based on the spatially weighted summation of the previously attributed criteria. Finally, flood susceptibility maps were generated for the different scenarios. The simulations of different rainfall patterns showed that this criterion profoundly influenced the likelihood to flood susceptibility. For the simulation of higher elevations and maximum rainfalls, the achieved index of flood susceptibility was 4 (out of 5). The main contribution of the study was the achievement of reliable parameters by the proposed techniques, that may also be used in other areas, mainly where data is scarce and complex physical constraints are involved, targeting the sustainable urban development of the regionDoutoradoRecursos Hidricos, Energeticos e AmbientaisDoutora em Engenharia Civi