A metaheuristic to solve the transmission expansion planning

In this letter, a genetic algorithm (GA) is applied to solve - the static and multistage transmission expansion planning (TEP) problem. The characteristics of the proposed GA to solve the TEP problem are presented. Results using some known systems show that the proposed GA solves a smaller number of linear programming problems in order to find the optimal solutions and obtains a better solution for the multistage TEP problem.

Evolutionary multi-move path-relinking for transmission network expansion planning

This paper presents the application of a new metaheuristic algorithm to solve the transmission expansion planning problem. A simple heuristic, using a relaxed network model associated with cost perturbation, is applied to generate a set of high quality initial solutions with different topologies. The population is evolved using a multi-move path-relinking with the objective of finding minimum investment cost for the transmission expansion planning problem employing the DC representation. The algorithm is tested on the southern Brazilian system, obtaining the optimal solution for the system with better performance than similar metaheuristics algorithms applied to the same problem. ©2010 IEEE.

Otimização do problema de carregamento de container usando uma metaheurística eficiente

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Arquitetura brutalista e estratégia de transportes no triângulo mineiro: estações ferroviárias da Mogiana e Terminal Rodoviário Presidente Castelo Branco

Em 1989, Brandão descrevia o Triângulo Mineiro como “fruto da ambiguidade de seu estigma de fazer parte de Minas, mas ser articulada economicamente a São Paulo.” A mesorregião do Triângulo Mineiro e Alto Paranaíba, faz fronteira com os estados de Goiás, São Paulo e Mato Grosso do Sul, interligando também com a Central Mineira e com o Oeste de Minas, sendo a característica de “rota de passagem” como principal fator do desenvolvimento de sua economia. O posicionamento estratégico da região, como eixo de ligação da capital paulista ao chamado Brasil Central, pode ser considerado um importante fator no estreitamento dos laços entre a região e São Paulo, somado ao sentimento de não pertencimento do Triângulo ao estado de Minas Gerais, o qual resultou por décadas em manifestações separatistas na região. A arquitetura moderna produzida no Triângulo Mineiro e Alto Paranaíba deu um salto significativo no momento de construção da nova capital federal, em finais da década de 1950, onde o papel de mediação, principalmente da cidade de Uberlândia, no processo de infra-estruturação da nova cidade foi determinante nos avanços construtivos do Triângulo. Esse momento coincidiu com o início do processo de verticalização das principais cidades da região e o aumento de arquitetos residentes nas cidades. Por meio, em especial, dos edifícios para as estações ferroviárias da Cia Mogiana, de Oswaldo Arthur Bratke em Uberaba e Uberlândia (déc. 1960) e do Terminal Rodoviário Presidente Castelo Branco em Uberlândia, dos arquitetos Fernando Graça, Flávio Almada e Ivan Curpertino (1970), este trabalho objetiva conduzir uma discussão acerca da produção de arquitetura moderna no Triângulo Mineiro ligada às estratégias de transportes intermunicipais como própria cultura de desenvolvimento econômico da região. Nos interessa valer do debate entre o uso da estética brutalista, e da própria escolha por uma arquitetura moderna, como artifício no plano de desenvolvimento das empresas de transporte, e dos governos locais. Sobretudo, discutir as interlocuções do Triângulo Mineiro com São Paulo, rebatendo-as na formação do conjunto arquitetonico moderno produzido na região. Este trabalho é fruto da pesquisa de mestrado da autora cujo tema central é a difusão da arquitetura moderna no Triângulo Mineiro e Alto Paranaíba, pelo Iau/Usp, e financiado pela Capes.

Stato attuale e prospettive di sviluppo del trasporto marittimo di container nei porti dell'alto adriatico

Le infrastrutture portuali rappresentano un elemento chiave come motore di crescita per l’economia globale. Il 74% delle merci importate ed esportate dall’UE transitano per porti. Per questo motivo sono necessari investimenti in infrastrutture e attrezzature portuali per far fronte alle previsioni di crescita del trasporto merci nel prossimo decennio. La crescita del transhipment, quindi di grossi scali chiamati hub, ha rivoluzionato la scelta delle tratte principali e la scelta degli scali. Nel corso del seguente elaborato ci si è concentrati sulla situazione dell’Alto Adriatico, analizzando lo stato attuale dei principali porti e i possibili sviluppi futuri. La situazione dell’Alto Adriatico è particolare, questi porti si trovano sulle rotte principali del trasporto globale ma vista la crescita di scambi commerciali con la Cina e l’estremo Oriente, per via dello spostamento verso Est del baricentro dell’economia, si trovano in posizione ottimale per diventare un grosso gateway. Questo è l’obbiettivo che si sono prefissati i porti del Nord Adriatico cioè far capire che risalire l’Adriatico, anche se fuori dalle rotte può risultare conveniente visto il risparmio di cinque giorni di navigazione, rispetto ai porti del Nord Europa, che si traduce in un risparmio di tempo e di costi. Per creare attrattiva sono stati svolti, e continuano, numerosi investimenti per lo sviluppo dei fondali e del retroporto, nel tentativo di potersi affermare all’interno del mercato europeo e globale. Nel corso dell’elaborato saranno analizzati i grossi vantaggi di cui godono i porti del Nord Adriatico grazie alla loro posizione geografica, e alcune delle problematiche che ostacolano la crescita.

Using ecological niche models to support tree species selection for forest restoration planning in largely deforested regions

Species selection for forest restoration is often supported by expert knowledge on local distribution patterns of native tree species. This approach is not applicable to largely deforested regions unless enough data on pre-human tree species distribution is available. In such regions, ecological niche models may provide essential information to support species selection in the framework of forest restoration planning. In this study we used ecological niche models to predict habitat suitability for native tree species in "Tierra de Campos" region, an almost totally deforested area of the Duero Basin (Spain). Previously available models provide habitat suitability predictions for dominant native tree species, but including non-dominant tree species in the forest restoration planning may be desirable to promote biodiversity, specially in largely deforested areas were near seed sources are not expected. We used the Forest Map of Spain as species occurrence data source to maximize the number of modeled tree species. Penalized logistic regression was used to train models using climate and lithological predictors. Using model predictions a set of tools were developed to support species selection in forest restoration planning. Model predictions were used to build ordered lists of suitable species for each cell of the study area. The suitable species lists were summarized drawing maps that showed the two most suitable species for each cell. Additionally, potential distribution maps of the suitable species for the study area were drawn. For a scenario with two dominant species, the models predicted a mixed forest (Quercus ilex and a coniferous tree species) for almost one half of the study area. According to the models, 22 non-dominant native tree species are suitable for the study area, with up to six suitable species per cell. The model predictions pointed to Crataegus monogyna, Juniperus communis, J.oxycedrus and J.phoenicea as the most suitable non-dominant native tree species in the study area. Our results encourage further use of ecological niche models for forest restoration planning in largely deforested regions.

Metodología para maximizar la rentabilidad de una terminal marítima de contenedores a través de la optimización de su grado de automatización

Son generalmente aceptadas las tendencias actuales de maximización de la automatización para la adaptación de las terminales marítimas de contenedores a las cada vez mayores exigencias competitivas del negocio de transporte de contenedores. En esta investigación, se somete a consideración dichas tendencias a través de un análisis que tenga en cuenta la realidad global de la terminal pero también su propia realidad local que le permita aprovechar sus fortalezas y minimizar sus debilidades en un mercado continuamente en crecimiento y cambio. Para lo cual se ha desarrollado un modelo de análisis en el que se tengan en cuenta los parámetros técnicos, operativos, económicos y financieros que influyen en el diseño de una terminal marítima de contenedores, desde su concepción como ente dependiente para generar negocio, todos ellos dentro de un perímetro definido por el mercado del tráfico de contenedores así como las limitaciones físicas introducidas por la propia terminal. Para la obtención de dicho modelo ha sido necesario llevar a cabo un proceso de estudio del contexto actual del tráfico de contenedores y su relación con el diseño de las terminales marítimas, así como de las metodologías propuestas hasta ahora por los diferentes autores para abordar el proceso de dimensionamiento y diseño de la terminal. Una vez definido el modelo que ha de servir de base para el diseño de una terminal marítima de contenedores desde un planteamiento multicriterio, se analiza la influencia de las diversas variables explicativas de dicho modelo y se cuantifica su impacto en los resultados económicos, financieros y operativos de la terminal. Un paso siguiente consiste en definir un modelo simplificado que vincule la rentabilidad de una concesión de terminal con el tráfico esperado en función del grado de automatización y del tipo de terminal. Esta investigación es el fruto del objetivo ambicioso de aportar una metodología que defina la opción óptima de diseño de una terminal marítima de contenedores apoyada en los pilares de la optimización del grado de automatización y de la maximización de la rentabilidad del negocio que en ella se desarrolla. It is generally accepted current trends in automation to maximize the adaptation of maritime container terminals to the growing competitive demands of the business of container shipping. In this research, is submitted to these trends through an analysis taking into account the global reality of the terminal but also their own local reality it could exploit its strengths and minimize their weaknesses in a market continuously growing and changing. For which we have developed a model analysis that takes into account the technical, operational, financial and economic influence in the design of a container shipping terminal, from its conception as being dependent to generate business, all within a perimeter defined by the market of container traffic and the physical constraints introduced by the terminal. To obtain this model has been necessary to conduct a study process in the current context of container traffic and its relation to the design of marine terminals, as well as the methodologies proposed so far by different authors to address the process sizing and design of the terminal. Having defined the model that will serve as the basis for the design for a container shipping terminal from a multi-criteria approach, we analyze the influence of various explanatory variables of the model and quantify their impact on economic performance, financial and operational of the terminal. A next step is to define a simplified model that links the profitability of a terminal concession with traffic expected on the basis of the degree of automation and the kind of terminal. This research is the result of the ambitious target of providing a methodology to define the optimal choice of designing a container shipping terminal on the pillars of automation optimizing and maximizing the profitability of the business that it develops.

Predicción de tráfico de contenedores a corto plazo mediante técnicas de minería de datos : redes neuronales artificiales y redes bayesianas

El correcto pronóstico en el ámbito de la logística de transportes es de vital importancia para una adecuada planificación de medios y recursos, así como de su optimización. Hasta la fecha los estudios sobre planificación portuaria se basan principalmente en modelos empíricos; que se han utilizado para planificar nuevas terminales y desarrollar planes directores cuando no se dispone de datos iniciales, analíticos; más relacionados con la teoría de colas y tiempos de espera con formulaciones matemáticas complejas y necesitando simplificaciones de las mismas para hacer manejable y práctico el modelo o de simulación; que requieren de una inversión significativa como para poder obtener resultados aceptables invirtiendo en programas y desarrollos complejos. La Minería de Datos (MD) es un área moderna interdisciplinaria que engloba a aquellas técnicas que operan de forma automática (requieren de la mínima intervención humana) y, además, son eficientes para trabajar con las grandes cantidades de información disponible en las bases de datos de numerosos problemas prácticos. La aplicación práctica de estas disciplinas se extiende a numerosos ámbitos comerciales y de investigación en problemas de predicción, clasificación o diagnosis. Entre las diferentes técnicas disponibles en minería de datos las redes neuronales artificiales (RNA) y las redes probabilísticas o redes bayesianas (RB) permiten modelizar de forma conjunta toda la información relevante para un problema dado. En el presente trabajo se han analizado dos aplicaciones de estos casos al ámbito portuario y en concreto a contenedores. En la Tesis Doctoral se desarrollan las RNA como herramienta para obtener previsiones de tráfico y de recursos a futuro de diferentes puertos, a partir de variables de explotación, obteniéndose valores continuos. Para el caso de las redes bayesianas (RB), se realiza un trabajo similar que para el caso de las RNA, obteniéndose valores discretos (un intervalo). El principal resultado que se obtiene es la posibilidad de utilizar tanto las RNA como las RB para la estimación a futuro de parámetros físicos, así como la relación entre los mismos en una terminal para una correcta asignación de los medios a utilizar y por tanto aumentar la eficiencia productiva de la terminal. Como paso final se realiza un estudio de complementariedad de ambos modelos a corto plazo, donde se puede comprobar la buena aceptación de los resultados obtenidos. Por tanto, se puede concluir que estos métodos de predicción pueden ser de gran ayuda a la planificación portuaria. The correct assets’ forecast in the field of transportation logistics is a matter of vital importance for a suitable planning and optimization of the necessary means and resources. Up to this date, ports planning studies were basically using empirical models to deal with new terminals planning or master plans development when no initial data are available; analytical models, more connected to the queuing theory and the waiting times, and very complicated mathematical formulations requiring significant simplifications to acquire a practical and easy to handle model; or simulation models, that require a significant investment in computer codes and complex developments to produce acceptable results. The Data Mining (DM) is a modern interdisciplinary field that include those techniques that operate automatically (almost no human intervention is required) and are highly efficient when dealing with practical problems characterized by huge data bases containing significant amount of information. These disciplines’ practical application extends to many commercial or research fields, dealing with forecast, classification or diagnosis problems. Among the different techniques of the Data Mining, the Artificial Neuronal Networks (ANN) and the probabilistic – or Bayesian – networks (BN) allow the joint modeling of all the relevant information for a given problem. This PhD work analyses their application to two practical cases in the ports field, concretely to container terminals. This PhD work details how the ANN have been developed as a tool to produce traffic and resources forecasts for several ports, based on exploitation variables to obtain continuous values. For the Bayesian networks case (BN), a similar development has been carried out, obtaining discreet values (an interval). The main finding is the possibility to use ANN and BN to estimate future needs of the port’s or terminal’s physical parameters, as well as the relationship between them within a specific terminal, that allow a correct assignment of the necessary means and, thus, to increase the terminal’s productive efficiency. The final step is a short term complementarily study of both models, carried out in order to verify the obtained results. It can thus be stated that these prediction methods can be a very useful tool in ports’ planning.

The Container tree nursery manual /

"March 2010"--V. 7.

Reauthorization of the Intermodal Surface Transportation Efficiency Act : hearings before the Subcommittee on Transportation and Infrastructure and the Committee on Environment and Public Works, United States Senate, One Hundred Fifth Congress, first session.

"March 22, 1997--Coeur d'Alene, Idaho ... May 7 and June 6, 1997--Washington, DC"--Pt. 2.

Collaborative Management of Intermodal Mobility

Part 21: Mobility and Logistics

Train scheduling in high speed railways: considering competitive effects

The railway planning problem is usually studied from two different points of view: macroscopic and microscopic. We propose a macroscopic approach for the high-speed rail scheduling problem where competitive effects are introduced. We study train frequency planning, timetable planning and rolling stock assignment problems and model the problem as a multi-commodity network flow problem considering competitive transport markets. The aim of the presented model is to maximize the total operator profit. We solve the optimization model using realistic probleminstances obtained from the network of the Spanish railwa operator RENFE, including other transport modes in Spain

Train scheduling and rolling stock assignment in high speed trains

The Train Timetabling Problem (TTP) has been widely studied for freight and passenger rail systems. A lesser effort has been devoted to the study of high-speed rail systems. A modeling issue that has to be addressed is to model departure time choice of passengers on railway services. Passengers who use these systems attempt to travel at predetermined hours due to their daily life necessities (e.g., commuter trips). We incorporate all these features into TTP focusing on high-speed railway systems. We propose a Rail Scheduling and Rolling Stock (RSch-RS) model for timetable planning of high-speed railway systems. This model is composed of two essential elements: i) an infrastructure model for representing the railway network: it includes capacity constraints of the rail network and the Rolling-Stock constraints; and ii) a demand model that defines how the passengers choose the departure time. The resulting model is a mixed-integer programming model which objective function attempts to maximize the profit for the rail operator