Um Modelo de otimização inteira mista na programação de produção de mangueiras hidráulicas

This work deals with a problem of mixed integer optimization model applied to production planning of a real world factory that aims for hydraulic hose production. To optimize production planning, a mathematic model of MILP Mixed Integer Linear Programming, so that, along with the Analytic Hierarchy process method, would be possible to create a hierarchical structure of the most import criteria for production planning, thus finding through a solving software the optimum hose attribution to its respective machine. The hybrid modeling of Analytic Hierarchy Process along with Linear Programming is the focus of this work. The results show that using this method we could unite factory reality and quantitative analysis and had success on improving performance of production planning efficiency regarding product delivery and optimization of the production flow

Fatores que Influenciam a flexibilidade da produção de veículos comerciais

Pós-graduação em Engenharia de Produção - FEG

Aplicação de métodos com múltiplos critérios em uma empresa petroquímica

The corporate world is increasingly competitive, and companies need to go deep into the routines and work them in order to understand them fully. The market is demanding more than simple improvements that bring advances - of small or great expression; however, in a longer term it will no longer meet the ideology of the market. Companies aimed at the world class must focus on projects that will continually bring returns to the company. As previously mentioned, understanding the processes in minute details is of paramount importance, as this knowledge can be acquired by analyzing the decisions that are necessary during the process. Once the complexity increases, the quantity and difficulty of the criteria that influence them grow accordingly. At this time, methods and tools that assist decisionmaking processes can be used as, besides being able to provide the best decision methods of MCDA (Multiple Criteria Decision Aid), they provide clear and assertive understanding of the whole decision process. In developing this study, we sought to explore the AHP (Analytic Hierarchy Process) method (a MCDA method) in the choice of access service, featured by the support service used to reach and be the basis of repairs in places of difficult access. This work proposes a study of the quantitative modeling approach in a real routine activity for a Brazilian petrochemical company. Decision-making processes are explored when we seek to analyze not only the decision makers but also what directly influences them on the use of the AIJ method. Once this is achieved, the understanding of decision-making is substantiated

Um Modelo de otimização inteira mista na programação de produção de mangueiras hidráulicas

This work deals with a problem of mixed integer optimization model applied to production planning of a real world factory that aims for hydraulic hose production. To optimize production planning, a mathematic model of MILP Mixed Integer Linear Programming, so that, along with the Analytic Hierarchy process method, would be possible to create a hierarchical structure of the most import criteria for production planning, thus finding through a solving software the optimum hose attribution to its respective machine. The hybrid modeling of Analytic Hierarchy Process along with Linear Programming is the focus of this work. The results show that using this method we could unite factory reality and quantitative analysis and had success on improving performance of production planning efficiency regarding product delivery and optimization of the production flow

Design and implementation of a multicriteria medical decision support system for diagnosis and treatment

Health care providers face the problem of trying to make decisions with inadequate information and also with an overload of (often contradictory) information. Physicians often choose treatment long before they know which disease is present. Indeed, uncertainty is intrinsic to the practice of medicine. Decision analysis can help physicians structure and work through a medical decision problem, and can provide reassurance that decisions are rational and consistent with the beliefs and preferences of other physicians and patients. ^ The primary purpose of this research project is to develop the theory, methods, techniques and tools necessary for designing and implementing a system to support solving medical decision problems. A case study involving “abdominal pain” serves as a prototype for implementing the system. The research, however, focuses on a generic class of problems and aims at covering theoretical as well as practical aspects of the system developed. ^ The main contributions of this research are: (1) bridging the gap between the statistical approach and the knowledge-based (expert) approach to medical decision making; (2) linking a collection of methods, techniques and tools together to allow for the design of a medical decision support system, based on a framework that involves the Analytic Network Process (ANP), the generalization of the Analytic Hierarchy Process (AHP) to dependence and feedback, for problems involving diagnosis and treatment; (3) enhancing the representation and manipulation of uncertainty in the ANP framework by incorporating group consensus weights; and (4) developing a computer program to assist in the implementation of the system. ^

CAOR: Context-aware Adaptive Opportunistic Routing in Mobile Ad-hoc Networks

Opportunistic routing (OR) employs a list of candidates to improve wireless transmission reliability. However, conventional list-based OR restricts the freedom of opportunism, since only the listed nodes are allowed to compete for packet forwarding. Additionally, the list is generated statically based on a single network metric prior to data transmission, which is not appropriate for mobile ad-hoc networks (MANETs). In this paper, we propose a novel OR protocol - Context-aware Adaptive Opportunistic Routing (CAOR) for MANETs. CAOR abandons the idea of candidate list and it allows all qualified nodes to participate in packet transmission. CAOR forwards packets by simultaneously exploiting multiple cross-layer context information, such as link quality, geographic progress, energy, and mobility.With the help of the Analytic Hierarchy Process theory, CAOR adjusts the weights of context information based on their instantaneous values to adapt the protocol behavior at run-time. Moreover, CAOR uses an active suppression mechanism to reduce packet duplication. Simulation results show that CAOR can provide efficient routing in highly mobile environments. The adaptivity feature of CAOR is also validated.

Enhancing multidirectional communication for cognitive cities

This paper presents the technical background and functionality of a meta-application (meta-app) for cognitive cities. This app enhances communication and thereby facilitates e-governance. This paper focuses on a user-centered implementation of the Fuzzy Analytical Hierarchy Process (FAHP) by presenting its technical specifications in relation with cognitive cities. For didactical reasons, a use case from the user perspective is included. Finally the findings are summed up and future work is presented

Adaptive Beaconless Opportunistic Routing for Multimedia Distribution

User experience on watching live videos must be satisfactory even under the inuence of different network conditions and topology changes, such as happening in Flying Ad-Hoc Networks (FANETs). Routing services for video dissemination over FANETs must be able to adapt routing decisions at runtime to meet Quality of Experience (QoE) requirements. In this paper, we introduce an adaptive beaconless opportunistic routing protocol for video dissemination over FANETs with QoE support, by taking into account multiple types of context information, such as link quality, residual energy, buffer state, as well as geographic information and node mobility in a 3D space. The proposed protocol takes into account Bayesian networks to define weight vectors and Analytic Hierarchy Process (AHP) to adjust the degree of importance for the context information based on instantaneous values. It also includes a position prediction to monitor the distance between two nodes in order to detect possible route failure.

Multi-criteria selection of structural adhesives to bond ABS parts obtained by rapid prototyping

One of the most used methods in rapidprototyping is Fused Deposition Modeling (FDM), which provides components with a reasonable strength in plastic materials such as ABS and has a low environmental impact. However, the FDM process exhibits low levels of surface finishing, difficulty in getting complex and/or small geometries and low consistency in “slim” elements of the parts. Furthermore, “cantilever” elements need large material structures to be supported. The solution of these deficiencies requires a comprehensive review of the three-dimensional part design to enhance advantages and performances of FDM and reduce their constraints. As a key feature of this redesign a novel method of construction by assembling parts with structuraladhesive joints is proposed. These adhesive joints should be designed specifically to fit the plastic substrate and the FDM manufacturing technology. To achieve this, the most suitable structuraladhesiveselection is firstly required. Therefore, the present work analyzes five different families of adhesives (cyanoacrylate, polyurethane, epoxy, acrylic and silicone), and, by means of the application of technical multi-criteria decision analysis based on the analytic hierarchy process (AHP), to select the structuraladhesive that better conjugates mechanical benefits and adaptation to the FDM manufacturing process

Diseño de un modelo de riesgo integral de incendios forestales mediante técnicas multicriterio y su automatización en sistemas de información geográfica : una aplicación en la Comunidad Valenciana

Los incendios forestales son la principal causa de mortalidad de árboles en la Europa mediterránea y constituyen la amenaza más seria para los ecosistemas forestales españoles. En la Comunidad Valenciana, diariamente se despliega cerca de un centenar de vehículos de vigilancia, cuya distribución se apoya, fundamentalmente, en un índice de riesgo de incendios calculado en función de las condiciones meteorológicas. La tesis se centra en el diseño y validación de un nuevo índice de riesgo integrado de incendios, especialmente adaptado a la región mediterránea y que facilite el proceso de toma de decisiones en la distribución diaria de los medios de vigilancia contra incendios forestales. El índice adopta el enfoque de riesgo integrado introducido en la última década y que incluye dos componentes de riesgo: el peligro de ignición y la vulnerabilidad. El primero representa la probabilidad de que se inicie un fuego y el peligro potencial para que se propague, mientras que la vulnerabilidad tiene en cuenta las características del territorio y los efectos potenciales del fuego sobre el mismo. Para el cálculo del peligro potencial se han identificado indicadores relativos a los agentes naturales y humanos causantes de incendios, la ocurrencia histórica y el estado de los combustibles, extremo muy relacionado con la meteorología y las especies. En cuanto a la vulnerabilidad se han empleado indicadores representativos de los efectos potenciales del incendio (comportamiento del fuego, infraestructuras de defensa), como de las características del terreno (valor, capacidad de regeneración…). Todos estos indicadores constituyen una estructura jerárquica en la que, siguiendo las recomendaciones de la Comisión europea para índices de riesgo de incendios, se han incluido indicadores representativos del riesgo a corto plazo y a largo plazo. El cálculo del valor final del índice se ha llevado a cabo mediante la progresiva agregación de los componentes que forman cada uno de los niveles de la estructura jerárquica del índice y su integración final. Puesto que las técnicas de decisión multicriterio están especialmente orientadas a tratar con problemas basados en estructuras jerárquicas, se ha aplicado el método TOPSIS para obtener la integración final del modelo. Se ha introducido en el modelo la opinión de los expertos, mediante la ponderación de cada uno de los componentes del índice. Se ha utilizado el método AHP, para obtener las ponderaciones de cada experto y su integración en un único peso por cada indicador. Para la validación del índice se han empleado los modelos de Ecuaciones de Estimación Generalizadas, que tienen en cuenta posibles respuestas correlacionadas. Para llevarla a cabo se emplearon los datos de oficiales de incendios ocurridos durante el período 1994 al 2003, referenciados a una cuadrícula de 10x10 km empleando la ocurrencia de incendios y su superficie, como variables dependientes. Los resultados de la validación muestran un buen funcionamiento del subíndice de peligro de ocurrencia con un alto grado de correlación entre el subíndice y la ocurrencia, un buen ajuste del modelo logístico y un buen poder discriminante. Por su parte, el subíndice de vulnerabilidad no ha presentado una correlación significativa entre sus valores y la superficie de los incendios, lo que no descarta su validez, ya que algunos de sus componentes tienen un carácter subjetivo, independiente de la superficie incendiada. En general el índice presenta un buen funcionamiento para la distribución de los medios de vigilancia en función del peligro de inicio. No obstante, se identifican y discuten nuevas líneas de investigación que podrían conducir a una mejora del ajuste global del índice. En concreto se plantea la necesidad de estudiar más profundamente la aparente correlación que existe en la provincia de Valencia entre la superficie forestal que ocupa cada cuadrícula de 10 km del territorio y su riesgo de incendios y que parece que a menor superficie forestal, mayor riesgo de incendio. Otros aspectos a investigar son la sensibilidad de los pesos de cada componente o la introducción de factores relativos a los medios potenciales de extinción en el subíndice de vulnerabilidad. Summary Forest fires are the main cause of tree mortality in Mediterranean Europe and the most serious threat to the Spanisf forest. In the Spanish autonomous region of Valencia, forest administration deploys a mobile fleet of 100 surveillance vehicles in forest land whose allocation is based on meteorological index of wildlandfire risk. This thesis is focused on the design and validation of a new Integrated Wildland Fire Risk Index proposed to efficient allocation of vehicles and specially adapted to the Mediterranean conditions. Following the approaches of integrated risk developed last decade, the index includes two risk components: Wildland Fire Danger and Vulnerability. The former represents the probability a fire ignites and the potential hazard of fire propagation or spread danger, while vulnerability accounts for characteristics of the land and potential effects of fire. To calculate the Wildland Fire Danger, indicators of ignition and spread danger have been identified, including human and natural occurrence agents, fuel conditions, historical occurrence and spread rate. Regarding vulnerability se han empleado indicadores representativos de los efectos potenciales del incendio (comportamiento del fuego, infraestructurasd de defensa), como de las características del terreno (valor, capacidad de regeneración…). These indicators make up the hierarchical structure for the index, which, following the criteria of the European Commission both short and long-term indicators have been included. Integration consists of the progressive aggregation of the components that make up every level in risk the index and, after that, the integration of these levels to obtain a unique value for the index. As Munticriteria methods are oriented to deal with hierarchically structured problems and with situations in which conflicting goals prevail, TOPSIS method is used in the integration of components. Multicriteria methods were also used to incorporate expert opinion in weighting of indicators and to carry out the aggregation process into the final index. The Analytic Hierarchy Process method was used to aggregate experts' opinions on each component into a single value. Generalized Estimation Equations, which account for possible correlated responses, were used to validate the index. Historical records of daily occurrence for the period from 1994 to 2003, referred to a 10x10-km-grid cell, as well as the extent of the fires were the dependant variables. The results of validation showed good Wildland Fire Danger component performance, with high correlation degree between Danger and occurrence, a good fit of the logistic model used and a good discrimination power. The vulnerability component has not showed a significant correlation between their values and surface fires, which does not mean the index is not valid, because of the subjective character of some of its components, independent of the surface of the fires. Overall, the index could be used to optimize the preventing resources allocation. Nevertheless, new researching lines are identified and discussed to improve the overall performance of the index. More specifically the need of study the inverse relationship between the value of the wildfire Fire Danger component and the forested surface of each 10 - km cell is set out. Other points to be researched are the sensitivity of the index component´s weight and the possibility of taking into account indicators related to fire fighting resources to make up the vulnerability component.

Analyzing climate change adaptation in the agriculture and water sectors: screening risks and opportunities.

As part of the Mediterranean area, the Guadiana basin in Spain is particularly exposed to increasing water stress due to climate change. Future warmer and drier climate will have negative implications for the sustainability of water resources and irrigation agriculture, the main socio- economic sector in the region. This paper illustrates a systematic analysis of climate change impacts and adaptation in the Guadiana basin based on a two-stage modeling approach. First, an integrated hydro-economic modeling framework was used to simulate the potential effects of regional climate change scenarios for the period 2000-2069. Second, a participatory multi-criteria technique, namely the Analytic Hierarchy Process (AHP), was applied to rank potential adaptation measures based on agreed criteria. Results show that, in the middle-long run and under severe climate change, reduced water availability, lower crop yields and increased irrigation demands might lead to water shortages, crop failure, and up to ten percent of income losses to irrigators. AHP results show how private farming adaptation measures, including improving irrigation efficiency and adjusting crop varieties, are preferred to public adaptation measures, such as building new dams. The integrated quantitative and qualitative methodology used in this research can be considered a socially-based valuable tool to support adaptation decision-making.

A multi-criteria optimization and decision-making approach for improvement of food engineering processes.

The objective of this study was to propose a multi-criteria optimization and decision-making technique to solve food engineering problems. This technique was demostrated using experimental data obtained on osmotic dehydratation of carrot cubes in a sodium chloride solution. The Aggregating Functions Approach, the Adaptive Random Search Algorithm, and the Penalty Functions Approach were used in this study to compute the initial set of non-dominated or Pareto-optimal solutions. Multiple non-linear regression analysis was performed on a set of experimental data in order to obtain particular multi-objective functions (responses), namely water loss, solute gain, rehydration ratio, three different colour criteria of rehydrated product, and sensory evaluation (organoleptic quality). Two multi-criteria decision-making approaches, the Analytic Hierarchy Process (AHP) and the Tabular Method (TM), were used simultaneously to choose the best alternative among the set of non-dominated solutions. The multi-criteria optimization and decision-making technique proposed in this study can facilitate the assessment of criteria weights, giving rise to a fairer, more consistent, and adequate final compromised solution or food process. This technique can be useful to food scientists in research and education, as well as to engineers involved in the improvement of a variety of food engineering processes.

Building resilience to water scarcity in Southern Spain: A case study of rice farming in Doñana protected wetlands

Agricultural water management needs to evolve in view of increased water scarcity, especially when farming and natural protected areas are closely linked. In the study site of Don?ana (southern Spain), water is shared by rice producers and a world heritage biodiversity ecosystem. Our aim is to contribute to defining adaptation strategies that may build resilience to increasing water scarcity and minimize water conflicts among agricultural and natural systems. The analytical framework links a participatory process with quantitative methods to prioritize the adaptation options. Bottom-up proposed adaptation measures are evaluated by a multi-criteria analysis (MCA) that includes both socioeconomic criteria and criteria of the ecosystem services affected by the adaptation options. Criteria weights are estimated by three different methods?analytic hierarchy process, Likert scale and equal weights?that are then compared. Finally, scores from an MCA are input into an optimization model used to determine the optimal land-use distribution in order to maximize utility and land-use diversification according to different scenarios of funds and water availability. While our results show a spectrum of perceptions of priorities among stakeholders, there is one overriding theme that is to define a way to restore part of the rice fields to natural wetlands. These results hold true under the current climate scenario and evenmore so under an increased water scarcity scenario.

Desarrollo de un algoritmo de decisión multicriterio para la gestión de listas de espera en la solicitud de Holter

Las listas de espera son un problema para la mayor parte de los países que cuentan con un Sistema Nacional de Salud. El presente trabajo propone analizar el problema de las listas de espera desde una perspectiva de Decisión Multicriterio. Tras un análisis de las diferentes metodologías existentes, hemos elaborado un modelo de decisión basado en el método AHP (Analytic Hierarchy Process) para la gestión de listas de espera y lo hemos aplicado a un Hospital de la Comunidad de Madrid. La decisión multicriterio MCDM (Multiple Criteria Decision Making) es la teoría que estudia y analiza los problemas de decisión que involucran diferentes criterios. La MCDM enmarca con precisión problemas reales de toma de decisiones, planteados usualmente haciendo uso de varios criterios en conflicto; en los cuales, no será posible obtener en general una solución que asigne a todos los criterios su mejor valor sino que el decisor, aplicando distintas técnicas, deberá decidir la mejor solución a escoger del conjunto de soluciones factibles. El fundamento del AHP radica en descomponer problemas complejos en otros más sencillos y agregar las soluciones de los mismos. Según la propuesta de Saaty, el primer paso para la aplicación de este método es estructurar jerárquicamente el problema en niveles con distintos nodos interconectados. El primer nivel de la jerarquía corresponde al propósito del problema, el nivel/niveles intermedios a los criterios/subcriterios en base a los cuales se forma la decisión y el último corresponde a las alternativas o soluciones factibles del problema. La aplicación del método AHP requiere: -Realizar comparaciones por pares entre los entes de cada nivel jerárquico, en base a la importancia que presentan para el nodo del nivel superior de la jerarquía al que están ligados. Los resultados de estas comparaciones se recogen en forma de matrices de comparación por pares. -Obtener los vectores de prioridad correspondientes a cada una de las matrices de comparación por pares. -Calcular la contribución de cada alternativa al propósito del problema, mediante una agregación multiplicativa entre los niveles jerárquicos y en función de estos valores, ordenar las alternativas y seleccionar lo más conveniente como solución del problema. Como último paso en la metodología AHP debemos señalar que, cualquiera que sea el método empleado para sintetizar la información de dichas matrices para determinar los vectores de prioridad de los entes que se comparan, es posible realizar un análisis de sensibilidad del resultado alcanzado, visualizando y analizando otras posibles soluciones a obtener haciendo cambios en los juicios de valor emitidos por la unidad decisora al construir dichas matrices. El software Expert-Choice permite realizar el análisis de sensibilidad de 5 formas diferentes. En estos análisis se realizan variaciones en el valor de un peso o prioridad y se observa numérica y gráficamente como este cambio afecta a la puntuación de las alternativas.

Procedimiento multicriterio-multiobjetivo de planificación energética a comunidades rurales aisladas

La toma de decisiones en el sector energético se torna compleja frente a las disímiles opciones y objetivos a cumplir. Para minimizar esta complejidad, se han venido desarrollando una gama amplia de métodos de apoyo a la toma de decisiones en proyectos energéticos. En la última década, las energización de comunidades rurales aisladas ha venido siendo prioridad de muchos gobiernos para mitigar las migraciones del campo para la ciudad. Para la toma de decisiones en los proyectos energéticos de comunidades rurales aisladas se necesitan proyectar la influencia que estos tendrás sobre los costes económicos, medioambientales y sociales. Es por esta razón que el presente trabajo tuvo como objetivo diseñar un modelo original denominado Generación Energética Autóctona Y Limpia (GEAYL) aplicado a una comunidad rural aislada de la provincia de Granma en Cuba. Este modelo parte dos modelos que le preceden el PAMER y el SEMA. El modelo GEAYL constituye un procedimiento multicriterio-multiobjetivo de apoyo a la planificación energética para este contexto. Se plantearon cinco funciones objetivos: F1, para la minimización de los costes energéticos; F2 para la minimización de las emisiones de CO2, F3, para la minimización de las emisiones de NOx; F4, para la minimización de las emisiones de SOx (cuyos coeficientes fueron obtenidos a través de la literatura especializada) y F5, para la maximización de la Aceptación Social de la Energía. La función F5 y la manera de obtener sus coeficientes constituye la novedad del presente trabajo. Estos coeficientes se determinaron aplicando el método AHP (Proceso Analítico Jerárquico) con los datos de partidas derivados de una encuesta a los usuarios finales de la energía y a expertos. Para determinar el suministro óptimo de energía se emplearon varios métodos: la suma ponderada, el producto ponderado, las distancias de Manhattan L1, la distancia Euclidea L2 y la distancia L3. Para estas métricas se aplicaron distintos vectores de pesos para determinar las distintas estructuras de preferencias de los decisores. Finalmente, se concluyó que tener en consideración a Aceptación Social de la Energía como una función del modelo influye en el suministro de energía de cada alternativa energética. ABSTRACT Energy planning decision making is a complex task due to the multiple options to follow and objectives to meet. In order to minimize this complexity, a wide variety of methods and supporting tools have been designed. Over the last decade, rural energization has been a priority for many governments, aiming to alleviate rural to urban migration. Rural energy planning decision making must rely on financial, environmental and social costs. The purpose of this work is to define an original energy planning model named Clean and Native Energy Generation (Generación Energética Autóctona Y Limpia, GEAYL), and carry out a case study on Granma Province, Cuba. This model is based on two previous models: PAMER & SEMA. GEAYL is a multiobjective-multicriteria energy planning model, which includes five functions to be optimized: F1, to minimize financial costs; F2, to minimize CO2 emissions; F3, to minimize NOx emissions; F4, to minimize SOx emissions; and F5, to maximize energy Social Acceptability. The coefficients corresponding to the first four functions have been obtained through specialized papers and official data, and the ones belonging to F5 through an Analytic Hierarchy Process (AHP), built as per a statistical enquiry carried out on energy users and experts. F5 and the AHP application are considered to be the novelty of this model. In order to establish the optimal energy supply, several methods have been applied: weighted sum, weighted product, Manhattan distance L1, Euclidean distance L2 and L3. Several weight vectors have been applied to the mentioned distances in order to conclude the decision makers potential preference structure. Among the conclusions of this work, it must be noted that function F5, Social Acceptability, has a clear influence on every energy supply alternative.