Diseño para fabricación digital: definición unívoca entre forma y fabricación en arquitectura

La presente investigación se inicia planteando el objetivo de identificar los parámetros geométricos que son exclusivos del proceso de generación de la Forma y relacionarlos con los invariantes relacionados con la Fabricación digital aplicada a la Arquitectura. Con ello se pretende recuperar la geometría como herramienta principal del proceso de Proyecto ampliando su ámbito de actuación al encontrar una relación con los procesos de fabricación digital. El primer capítulo describe los antecedentes y contexto histórico centrándose especialmente en la influencia de la capacidad de definir geometrías complejas digitalmente mediante la aplicación de algoritmos. En los primeros ejemplos la aproximación del Arquitecto a proyectos con geometrías complejas no euclídeas aún se emplea sin precisión en la comunicación de la geometría ideada para su puesta en obra. Las técnicas constructivas obligan a asumir una tolerancia de desviación entre proyecto y obra y la previsión del comportamiento de esa geometría no permite asegurar su comportamiento final. No será hasta la introducción de herramientas CAD en el proceso de ideación arquitectónica cuando el Arquitecto se capacite para generar geometrías no representables de forma analógica. Sin embargo, la imposibilidad de trasladar la geometría proyectada a la praxis constructiva impedirá la plasmación de un proceso completo, salvo en las contadas ocasiones que se recogen en este texto. “El análisis cronológico de las referencias establece como aspecto esencial para la construcción de geometrías complejas la capacidad primero para definir y comunicar de forma precisa e inequívoca la geometría y después la capacidad de analizar el desempeño prestacional de dicha propuesta geométrica”. La presente investigación se inicia planteando el objetivo de identificar los parámetros geométricos que son exclusivos del proceso de generación de la Forma y relacionarlos con los invariantes relacionados con la Fabricación digital aplicada a la Arquitectura. Con ello se pretende recuperar la geometría como herramienta principal del proceso de Proyecto ampliando su ámbito de actuación al encontrar una relación con los procesos de fabricación digital. El primer capítulo describe los antecedentes y contexto histórico centrándose especialmente en la influencia de la capacidad de definir geometrías complejas digitalmente mediante la aplicación de algoritmos. En los primeros ejemplos la aproximación del Arquitecto a proyectos con geometrías complejas no euclídeas aún se emplea sin precisión en la comunicación de la geometría ideada para su puesta en obra. Las técnicas constructivas obligan a asumir una tolerancia de desviación entre proyecto y obra y la previsión del comportamiento de esa geometría no permite asegurar su comportamiento final. No será hasta la introducción de herramientas CAD en el proceso de ideación arquitectónica cuando el Arquitecto se capacite para generar geometrías no representables de forma analógica. Sin embargo, la imposibilidad de trasladar la geometría proyectada a la praxis constructiva impedirá la plasmación de un proceso completo, salvo en las contadas ocasiones que se recogen en este texto. “El análisis cronológico de las referencias establece como aspecto esencial para la construcción de geometrías complejas la capacidad primero para definir y comunicar de forma precisa e inequívoca la geometría y después la capacidad de analizar el desempeño prestacional de dicha propuesta geométrica”. Establecida la primera conclusión, el capítulo de contexto histórico continúa enfocándose sobre la aplicación de las técnicas digitales en el Proceso de proyecto primero, y en la puesta en obra después. Los casos de estudio identifican claramente como un punto de inflexión para la generación de formas complejas mediante un software CAD el Museo Guggenheim de Bilbao en 1992. El motivo esencial para elegir este proyecto como el primer proyecto digital es el uso de la herramienta de definición digital de la geometría para su reproducción inequívoca en obra. “La revolución digital ha aportado al Arquitecto la posibilidad de abandonar las tipologías arquitectónicas basados en restricciones geométricas-constructivas. La aplicación de técnicas de fabricación digital ha permitido la capacidad de diseñar con independencia del sistema constructivo y libertad formal. En este nuevo contexto las prestaciones suponen los nuevos límites conceptuales, ya que el acceso y disposición de la información del comportamiento de las alternativas que cada geometría conlleva demanda del Arquitecto la jerarquización de los objetivos y la formulación en un conjunto coherente de parámetros”. Los proyectos que emplean herramientas digitales para la resolución de las distintas etapas del proceso proyectual se verán incrementados de forma exponencial desde 1992 hasta nuestros días. A pesar del importante auge de las técnicas de diseño asistido por ordenador el principal desafío sigue siendo la vinculación de las geometrías y materiales propuestos con las capacidades de las técnicas de manufactura y puesta en obra. El proceso de diseño para fabricación en un entorno digital es una tecnología madura en otras industrias como la aeroespacial o la automovilística, incluso la de productos de consumo y decoración, sin embargo en el sector de Construcción es un sistema inmaduro e inconexo. Las particularidades de la industria de la construcción aún no han sido abordadas en su totalidad y las propuestas de investigación realizadas en este ámbito se han centrado hasta 2015 en partes del proceso y no en el proceso total. “El principal obstáculo para la estandarización e implantación globalizada de un proceso digital desde el origen de la forma hasta la construcción es la inexistencia de un protocolo integrado que integre las limitaciones de fabricación, económicas y de puesta en obra junto a la evaluación de desempeño prestacional durante la fases iniciales de proyecto”. En el capítulo número 3 se estudian los distintos procesos de generación de la forma. Se propone una definición específica para el ámbito de la investigación de “forma” en el entendemos que se incluye la envolvente exterior y el conjunto organizativo de espacios interiores conectados. Por lo tanto no es excluyente del interior. El objetivo de este estudio es analizar y clasificar los procesos para la generación digital de formas en los distintos proyectos seleccionados como emblemáticos de cada tipología. Se concluye que la aproximación a este proceso es muy variada y compleja, con aplicación segregada y descoordinada entre los distintos agentes que han intervenir. En un proceso de generación formal analógico los parámetros que intervienen son en parte conscientes y en parte inconscientes o aprendidos. El Arquitecto sólo tiene control sobre la parte consciente de los parámetros a integrar en el diseño, de acuerdo a sus conocimientos y capacidades será capaz de manejar un número limitado de parámetros. La parte aprendida permanece en el inconsciente y dirige el proceso analógico, aportando prejuicios estéticos incorporados durante el proceso formativo y propio del entorno cultural. “El empleo de herramientas digitales basadas en la evaluación prestacional durante el proceso de selección formal permite al Arquitecto conocer “en tiempo real” el desempeño en el conjunto de prestaciones evaluadoras del conjunto de alternativas geométricas a la propuesta previamente definida por la intuición arquitectónica. El proceso definido no persigue identificar una solución óptima sino asistir al Arquitecto en el proceso de generación de la forma mediante la evaluación continua de los vectores direccionales más idóneos que el procedimiento generativo plantea”. La definición de complejidad en generación y producción de formas en relación con el proceso de diseño digital paramétrico global o integrado, es esencial para establecer un protocolo que optimice su gestión. “Se propone como definición de complejidad como factor resultante de multiplicar el número de agentes intervinientes por el número de parámetros e interacciones comunes que intervienen en el proceso de generación de la forma, dividido por la complejidad de intercambio de información digital desde el origen hasta la fase de fabricación y construcción”. Una vez analizados los procesos de generación digital de Arquitectura se propone identificar los parámetros geométricos que definen el proceso de Diseño digital, entendiendose por Diseño el proceso que engloba desde la proposición de una forma inicial basada en la intuición del Arquitecto, la generación y evaluación de variantes y posterior definición digital para producción, tanto de un objeto, un sistema o de la totalidad del Proyecto. En la actualidad el proceso de Diseño es discontinuo y lineal organizandose los parámetros por disciplinas en las que está estructurada las atribuciones profesionales en la industria de la construcción. Para simplificar la identificación y listado se han agrupado siguiendo estos grupos de conocimiento. Entendemos parametros invariables aquellos que son independientes de Tipologías arquitectónicas o que dependen del mismo proceso de generación de la Forma. “El listado de los parámetros que intervienen en un proceso de generación formal es una abstracción de una realidad compleja. La parametrización de las decisiones que intervienen en la selección de una forma determinada mediante “well defined problems” es imposible. El proceso que esta tesis describe entiende esta condición como un elemento que pone en valor el propio procedimiento generativo por la riqueza que la subjetividad que el equipo de diseño aporta”. La segunda parte esencial de esta investigación pretende extraer las restricciones propias del estado del arte de la fabricación digital para posteriormente incorporarlos en los procesos digitales de definición de la Forma arquitectónica. “La integración de las restricciones derivadas de las técnicas de fabricación y construcción digitales en el proceso de generación de formas desde el ámbito de la Arquitectura debe referirse a los condicionantes geométricos asociados a cada sistema constructivo, material y técnica de fabricación. La geometría es además el vínculo que permite asociar el conjunto de parámetros prestacionales seleccionados para un Proyecto con los sistemas de fabricación digital”. A estos condicionantes geométricos obtenidos del análisis de cada sistema de fabricación digital se les ha denominado “invariantes geométricos”. Bajo este término se engloban tanto límites dimensionales de fabricación, como materiales compatibles, tolerancias de manufactura e instalación y cualidades prestacionales asociadas. El objetivo de esta propuesta es emplear la geometría, herramienta fundamental y propia del Arquitecto, como nexo de unión entre el conjunto complejo y heterogéneo de parámetros previamente listados y analizados. Para ello se han simplificado en tablas específicas para cada parámetro prestacional los condicionantes geométricos que se derivan de los Sistemas de fabricación digital compatibles (ver apéndice 1). El estudio y evaluación de las capacidades y objetivos de las distintas plataformas de software disponibles y de las experiencias profesionales evaluadas en los proyectos presentados, permiten concluir que la propuesta de plataforma digital de diseño integral multi-paramétrico de formas arquitectónicas requiere de un protocolo de interoperatibilidad específico aún no universalmente establecido. Actualmente el enfoque de la estrategia para normalizar y universalizar el contexto normativo para regular la interoperatibilidad se centra en figura del gestor denominado “BIM manager”. Las atribuciones y roles de esta figura se enfocan a la gestión del continente y no del contenido (Definición de los formatos de intercambio, niveles de desarrollo (LOD) de los componentes o conjuntos constructivos, detección de interferencias y documentación del propio modelo). Siendo este ámbito un desarrollo necesario para la propuesta de universalización del sistema de diseño para fabricación digital integrado, la presente investigación aporta un organigrama y protocolo asociado. El protocolo: 1. Establece la responsabilidad de identificar y definir la Información que debe determinar el proceso de generación y desarrollo de la forma arquitectónica. 2. Define la forma digital apropiada para generar la geometría del Proyecto, incluyendo la precisión necesaria para cada componente y el nivel de detalle necesario para su exportación inequívoca al proceso de fabricación. 3. Define el tempo de cada etapa de diseño identificando un nivel de detalle acorde. 4. Acopla este organigrama dentro de las estructuras nuevas que se proponen en un entorno BIM para asegurar que no se producen solapes o vacíos con las atribuciones que se identifican para el BIM Manager. “El Arquitecto debe dirigir el protocolo de generación coordinada con los sistemas de producción digital para conseguir que la integración completa. El protocolo debe asistir al proceso de generación de forma mediante la evaluación del desempeño prestacional de cada variante en tiempo real. La comunicación entre herramientas digitales es esencial para permitir una ágil transmisión de información. Es necesario establecer un protocolo adaptado a los objetivos y las necesidades operativas de cada proyecto ya que la estandarización de un protocolo único no es posible”. Una decisión estratégica a la hora de planificar una plataforma de diseño digital común es establecer si vamos a optar por un Modelo digital único o diversos Modelos digitales federados. Cada uno de los modos de trabajo tiene fortalezas y debilidades, no obstante en el ámbito de investigación se ha concluido que un proceso integrado de Diseño que incorpore la evaluación prestacional y conceptual definida en el Capítulo 3, requiere necesariamente de varios modelos de software distintos que han de relacionarse entre sí mediante un protocolo de comunicación automatizado. Una plataforma basada en un modelo federado consiste en establecer un protocolo de comunicación entre los programas informáticos empleados por cada disciplina. En este modelo de operación cada equipo de diseño debe establecer las bases de comunicación en función del número y tipo de programas y procesos digitales a emplear. En esta investigación se propone un protocolo basado en los estándares de intercambio de información que estructura cualquier proceso de generación de forma paramétrico “La investigación establece el empleo de algoritmos evolutivos como el sistema actual óptimo para desarrollar un proceso de generación de formas basadas en la integración y coordinación de invariantes geométricos derivados de un conjunto de objetivos prestacionales y constructivos. No obstante, para la aplicación en el caso práctico realizado se ha podido verificar que la evaluación del desempeño aún no puede realizarse en una única herramienta y por lo tanto el proceso de selección de las variantes genéticas óptimas ha de ejecutarse de forma manual y acumulativa. El proceso debe realizarse de manera federada para la selección evolutiva de los invariantes geométricos dimensionales”. La evaluación del protocolo de integración y los condicionantes geométricos obtenidos como parámetros geométricos que controlan las posibles formas compatibles se realiza mediante su aplicación en un caso práctico. El ejercicio simula la colaboración multidisciplinar con modelos federados de plataformas distintas. La elección del tamaño y complejidad constructiva del proyecto se ha modulado para poder alcanzar un desarrollo completo de cada uno de los parámetros prestacionales seleccionados. Continuando con el mismo objetivo propuesto para los parámetros prestacionales, la tipología constructiva-estructural seleccionada para el ejercicio permite la aplicación la totalidad de invariantes geométricos asociados. El objetivo de este caso práctico es evaluar la capacidad alterar la forma inicialmente propuesta mediante la evaluación del desempeño prestacional de conjunto de variantes geométricas generadas a partir de un parámetro dimensional determinado. Para que este proceso tenga sentido, cada una de las variantes debe ser previamente validada conforme a las limitaciones geométricas propias de cada sistema de fabricación y montaje previstos. El interés de las conclusiones obtenidas es la identificación de una variante geométrica distante a la solución simétrica inicialmente como la solución óptima para el conjunto de parámetros seleccionados. Al tiempo se ha comprobado como la participación de un conjunto de parámetros multi-disciplinares que representan la realidad compleja de los objetivos arquitectónicos favorecen la aparición de variaciones genéticas con prestaciones mejoradas a la intuición inicial. “La herencias tipológicas suponen un límite para la imaginación de variantes formales al proceso de ideación arquitectónica. El ejercicio realizado demuestra que incluso en casos donde aparentemente la solución óptima aparenta ser obvia una variante aleatoria puede mejorar su desempeño global. La posibilidad de conocer las condiciones geométricas de las técnicas de fabricación digital compatibles con el conjunto de parámetros seleccionados por el Arquitecto para dirigir el proceso asegura que los resultados del algoritmo evolutivo empleado sean constructivamente viables. La mejora de imaginación humana con la aportación de geometrías realmente construibles supone el objetivo último de esta tesis”. ABSTRACT Architectural form generation process is shifting from analogical to digital. Digital technology has changed the way we design empowering Architects and Engineers to precisely define any complex geometry envisioned. At the same time, the construction industry, following aeronautical and automotive industries, is implementing digital manufacturing techniques to improve efficiency and quality. Consequently construction complexity will no longer be related to geometry complexity and it is associated to coordination with digital manufacturing capacities. Unfortunately it is agreed that non-standard geometries, even when proposed with performance optimization criteria, are only suitable for projects with non-restricted budgets. Furthemore, the lack of coordinated exportation protocol and geometry management between design and construction is avoiding the globalization of emergence process in built projects Present research first objective is to identify exclusive form-generation parameters related to digital manufacturing geometrical restraints. The intention was to use geometry as the form-generation tool and integrate the digital manufacturing capacities at first stages of the project. The first chapter of this text describes the investigation historical context focusing on the influence between accurate geometry definition at non-standard forms and its construction. At first examples of non-Euclidean geometries built the communication between design and construction were based on analogical partial and imprecise documentation. Deficient communication leads to geometry adaptation on site leaving the final form uncontrolled by the Architect. Computer Aided Design enable Architects to define univocally complex geometries that previously where impossible to communicate. “The univocally definition of the Form, and communication between design and construction is essential for complex geometry Projects”. The second chapter is focused on digital technologies application in form finding process and site construction. The case studies selected identifies a clear inflexion node at 1992 with the Guggenheim Museum in Bilbao. The singularity of this project was the use of Aeronautics software to define digitally the external envelope complex geometry to enable the contractor to build it. “The digital revolution has given the Architect the capacity to design buildings beyond the architectural archetypes driven by geometric-constructive limitations. The application of digital manufacturing techniques has enabled a free-form construction without geometrical limitations. In this new context performance shall be the responsible to set new conceptual boundaries, since the behavior of each possible geometry can be compare and analyze beforehand. The role of the Architect is to prioritize the performance and architectural objectives of each project in a complete and coherent set of parameters”. Projects using digital tools for solving various stages of the design process were increased exponentially since 1992 until today. Despite the significant rise of the techniques of computer-aided design the main challenge remains linking geometries and materials proposed at each design with the capabilities of digital manufacturing techniques. Design for manufacturing in a digital environment is a mature technology in other industries such as aerospace and automotive, including consumer products and decoration, but in the construction sector is an immature and disjointed system. The peculiarities of the construction industry have not yet been addressed in its entirety and research proposals made in this area until 2015 have focused in separate parts of the process and not the total process. “The main obstacle to global standardization and implementation of a complete digital process from the form-finding to construction site is the lack of an integrated protocol that integrates manufacturing, economic and commissioning limitations, together with the performance evaluation of each possible form”. The different form generation processes are studied at chapter number 3. At the introduction of this chapter there is a specific definition of "form" for the research field. Form is identified with the outer envelope geometry, including the organizational set of connected indoor spaces connected to it. Therefore it is not exclusive of the interior. The aim of this study is to analyze and classify the main digital form generation processes using different selected projects as emblematic of each type. The approach to this process is complex, with segregated and uncoordinated different actors have to intervene application. In an analogical form-generation process parameters involved are partly conscious and partly unconscious or learned. The architect has control only over limited part of the parameters to be integrated into the design, according to their knowledge and. There is also a learned aesthetical prejudice that leads the form generation process to a specific geometry leaving the performance and optimization criteria apart from the decision making process. “Using performance evaluation digital tools during form finding process provides real-time comparative information to the Architect enabling geometry selection based on its performance. The generative form generation process described at this document does not ambition to identify the optimum geometry for each set of parameters. The objective is to provide quick information at each generation of what direction is most favorable for the performance parameters selected”. Manufacturing complexity definition in relation to a global and integral process of digital design for manufacture is essential for establishing an efficient managing protocol. “The definition of complexity associated to design for production in Architecture is proposed as the factor between number of different agents involved in the process by the number of interactions required between them, divided by the percentage of the interchange of information that is standardized and proof of information loss”. Design in architecture is a multi-objective process by definition. Therefore, addressing generation process linked to a set of non-coherent parameters requires the selection of adequate generative algorithm and the interaction of the architect. During the second half of the twentieth century and early twenty-first century it have been developed various mathematical algorithms for multi-parametric digital design. Heuristic algorithms are the most adequate algorithms for architectural projects due to its nature. The advantage of such algorithms is the ability to efficiently handle large scale optimization cases where a large number of design objectives and variables are involved. These generative processes do not pursue the optimum solution, in fact it will be impossible to proof with such algorithm. This is not a problem in architectural design where the final goal is to guide the form finding process towards a better performance within the initial direction provided by the architect. This research has focused on genetic algorithms due to its capacity to generate geometric alternatives in multiple directions and evaluate the fitness against a set of parameters specified in a single process. "Any protocol seeks to achieve standardization. The design to manufacturing protocol aims to provide a coordinated and coherent form generation process between a set of design parameters and the geometrical requirements of manufacturing technique. The protocol also provides an information exchange environment where there is a communication path and the level of information is ensured. The research is focused on the process because it is considered that each project will have its own singularities and parameters but the process will stay the same. Again the development of a specific tool is not a goal for the research, the intention is to provide an open source protocol that is valid for any set of tools”. Once the digital generation processes are being analized and classified, the next step is to identify the geometric parameters that define the digital design process. The definition of design process is including from the initial shape proposal based on the intuition of the architect to the generation, evaluation, selection and production of alternatives, both of an object , system or of the entire project . The current design process in Architecture is discontinuous and linear, dividing the process in disciplines in which the construction industry is structured. The proposal is to unify all relevant parameters in one process. The parameters are listed in groups of knowledge for internal classification but the matrix used for parameter relationship determination are combined. “A multi-parameter determination of the form-finding process is the integration all the measurable decisions laying behind Architect intuition. It is not possible to formulate and solve with an algorithm the design in Architecture. It is not the intention to do so with the proposal of this research. The process aims to integrate in one open protocol a selection of parameters by using geometry as common language. There is no optimum solution for any step of the process, the outcome is an evaluation of performance of all the form variations to assist the Architect for the selection of the preferable solution for the project”. The research follows with the geometrical restrictions of today Digital manufacturing techniques. Once determined it has been integrated in the form-finding process. “Digital manufacturing techniques are integrated in the form-finding process using geometry as common language. Geometric restraints define the boundary for performance parametric form-finding process. Geometrical limitations are classified by material and constructive system”. Choose between one digital model or several federate models is a strategic decision at planning a digital design for manufacturing protocol. Each one of the working models have strengths and weakens, nevertheless for the research purposes federated models are required to manage the different performance evaluation software platforms. A protocol based on federated models shall establish a communication process between software platforms and consultants. The manager shall integrate each discipline requirements defining the communication basis. The proposed protocol is based on standards on information exchange with singularities of the digital manufacturing industry. “The research concludes evolutionary algorithms as current best system to develop a generative form finding process based on the integration and coordination of a set of performance and constructive objectives. However, for application in professional practice and standardize it, the performance evaluation cannot be done in only one tool and therefore the selection of optimal genetic variants must be run in several iterations with a cumulative result. Consequently, the evaluation process within the geometrical restraints shall be carried out with federated models coordinated following the information exchange protocol”. The integration protocol and geometric constraints evaluation is done by applying in a practical case study. The exercise simulates multidisciplinary collaboration across software platforms with federated models. The choice of size and construction complexity of the project has been modulated to achieve the full development of each of the parameters selected. Continuing with the same objective proposed for the performance parameters the constructive and structural type selected for the exercise allows the application all geometric invariants associated to the set of parameters selected. The main goal of the case study is to proof the capacity of the manufacturing integrated form finding process to generate geometric alternatives to initial form with performance improved and following the restrictions determined by the compatible digital manufacturing technologies. The process is to be divided in consecutive analysis each one limited by the geometrical conditions and integrated in a overall evaluation. The interest of this process is the result of a non-intuitive form that performs better than a double symmetrical form. The second conclusion is that one parameter evaluation alone will not justify the exploration of complex geometry variations, but when there is a set of parameters with multidisciplinary approach then the less obvious solution emerge as the better performing form. “Architectural typologies impose limitation for Architects capacity to imagine formal variations. The case study and the research conclusions proof that even in situations where the intuitive solution apparently is the optimum solution, random variations can perform better when integrating all parameters evaluation. The capacity of foreseing the geometrical properties linking each design parameter with compatible manufacturing technologies ensure the result of the form-finding process to be constructively viable. Finally, the propose of a complete process where the geometry alternatives are generated beyond the Architect intuition and performance evaluated by a set of parameters previously selected and coordinated with the manufacturing requirements is the final objective of the Thesis”.

Planejamento de sistemas de distribuição de energia elétrica considerando questões de confiabilidade e risco

O problema de Planejamento da Expansão de Sistemas de Distribuição (PESD) visa determinar diretrizes para a expansão da rede considerando a crescente demanda dos consumidores. Nesse contexto, as empresas distribuidoras de energia elétrica têm o papel de propor ações no sistema de distribuição com o intuito de adequar o fornecimento da energia aos padrões exigidos pelos órgãos reguladores. Tradicionalmente considera-se apenas a minimização do custo global de investimento de planos de expansão, negligenciando-se questões de confiabilidade e robustez do sistema. Como consequência, os planos de expansão obtidos levam o sistema de distribuição a configurações que são vulneráveis a elevados cortes de carga na ocorrência de contingências na rede. Este trabalho busca a elaboração de uma metodologia para inserir questões de confiabilidade e risco ao problema PESD tradicional, com o intuito de escolher planos de expansão que maximizem a robustez da rede e, consequentemente, atenuar os danos causados pelas contingências no sistema. Formulou-se um modelo multiobjetivo do problema PESD em que se minimizam dois objetivos: o custo global (que incorpora custo de investimento, custo de manutenção, custo de operação e custo de produção de energia) e o risco de implantação de planos de expansão. Para ambos os objetivos, são formulados modelos lineares inteiros mistos que são resolvidos utilizando o solver CPLEX através do software GAMS. Para administrar a busca por soluções ótimas, optou-se por programar em linguagem C++ dois Algoritmos Evolutivos: Non-dominated Sorting Genetic Algorithm-2 (NSGA2) e Strength Pareto Evolutionary Algorithm-2 (SPEA2). Esses algoritmos mostraram-se eficazes nessa busca, o que foi constatado através de simulações do planejamento da expansão de dois sistemas testes adaptados da literatura. O conjunto de soluções encontradas nas simulações contém planos de expansão com diferentes níveis de custo global e de risco de implantação, destacando a diversidade das soluções propostas. Algumas dessas topologias são ilustradas para se evidenciar suas diferenças.

Logística operacional: alocação de bases operacionais em distribuição de energia elétrica.

Ser eficiente é um requisito para a sustentabilidade das empresas concessionárias de distribuição de energia elétrica no Brasil. A busca pela eficiência deve estar em harmonia com a melhoria contínua da qualidade, da segurança e da satisfação dos consumidores e das partes envolvidas. O desafio de atender múltiplos objetivos requer que as empresas do setor desenvolvam soluções inovadoras, com a mudança de processos, tecnologia, estrutura e a capacitação das pessoas. Desenvolver um modelo operacional eficiente e uma gestão rigorosa dos custos são fatores-chave para o sucesso das empresas, considerando o contexto regulatório de revisão tarifária que incentiva a melhoria do desempenho. O modelo operacional é definido a partir da organização logística dos recursos para atendimento da demanda de serviços, que define também os custos fixos e variáveis de pessoal (salário, horas extras, refeições), infraestrutura (manutenção de prédios, ferramentas e equipamentos) e deslocamentos (manutenção de veículos, combustível), por exemplo. A melhor alocação e o melhor dimensionamento de bases operacionais possibilitam a redução dos custos com deslocamento e infraestrutura, favorecendo o aproveitamento da força de trabalho em campo, a melhoria do atendimento dos clientes e da segurança dos colaboradores. Este trabalho apresenta uma metodologia de otimização de custos através da alocação de bases e equipes operacionais, com o modelamento matemático dos objetivos e restrições do negócio e a aplicação de algoritmo evolutivo para busca das melhores soluções, sendo uma aplicação de Pesquisa Operacional, no campo da Localização de Instalações, em distribuição de energia elétrica. O modelo de otimização desenvolvido possibilita a busca pelo ponto de equilíbrio ótimo que minimiza o custo total formado pelos custos de infraestrutura, frota (veículos e deslocamentos) e pessoal. O algoritmo evolutivo aplicado no modelo oferece soluções otimizadas pelo melhoramento de conjuntos de variáveis binárias com base em conceitos da evolução genética. O modelo de otimização fornece o detalhamento de toda a estrutura operacional e de custos para uma determinada solução do problema, utilizando premissas de produtividade e deslocamentos (velocidades e distâncias) para definir as abrangências de atuação das bases operacionais, recursos (equipes, pessoas, veículos) necessários para atendimento da demanda de serviços, e projetar todos os custos fixos e variáveis associados. A metodologia desenvolvida neste trabalho considera também a projeção de demanda futura para a aplicação no estudo de caso, que evidenciou a efetividade da metodologia como ferramenta para a melhoria da eficiência operacional em empresas de distribuição de energia elétrica.

Grouping genetic operators for the delineation of functional areas based on spatial interaction

The delineation of functional economic areas, or market areas, is a problem of high practical relevance, since the delineation of functional sets such as economic areas in the US, Travel-to-Work Areas in the United Kingdom, and their counterparts in other OECD countries are the basis of many statistical operations and policy making decisions at local level. This is a combinatorial optimisation problem defined as the partition of a given set of indivisible spatial units (covering a territory) into regions characterised by being (a) self-contained and (b) cohesive, in terms of spatial interaction data (flows, relationships). Usually, each region must reach a minimum size and self-containment level, and must be continuous. Although these optimisation problems have been typically solved through greedy methods, a recent strand of the literature in this field has been concerned with the use of evolutionary algorithms with ad hoc operators. Although these algorithms have proved to be successful in improving the results of some of the more widely applied official procedures, they are so time consuming that cannot be applied directly to solve real-world problems. In this paper we propose a new set of group-based mutation operators, featuring general operations over disjoint groups, tailored to ensure that all the constraints are respected during the operation to improve efficiency. A comparative analysis of our results with those from previous approaches shows that the proposed algorithm systematically improves them in terms of both quality and processing time, something of crucial relevance since it allows dealing with most large, real-world problems in reasonable time.

FPGA implementation of a multi-population PBIL algorithm

Evolutionary-based algorithms play an important role in finding solutions to many problems that are not solved by classical methods, and particularly so for those cases where solutions lie within extreme non-convex multidimensional spaces. The intrinsic parallel structure of evolutionary algorithms are amenable to the simultaneous testing of multiple solutions; this has proved essential to the circumvention of local optima, and such robustness comes with high computational overhead, though custom digital processor use may reduce this cost. This paper presents a new implementation of an old, and almost forgotten, evolutionary algorithm: the population-based incremental learning method. We show that the structure of this algorithm is well suited to implementation within programmable logic, as compared with contemporary genetic algorithms. Further, the inherent concurrency of our FPGA implementation facilitates the integration and testing of micro-populations.

Population-based continuous optimization, probabilistic modelling and mean shift

Evolutionary algorithms perform optimization using a population of sample solution points. An interesting development has been to view population-based optimization as the process of evolving an explicit, probabilistic model of the search space. This paper investigates a formal basis for continuous, population-based optimization in terms of a stochastic gradient descent on the Kullback-Leibler divergence between the model probability density and the objective function, represented as an unknown density of assumed form. This leads to an update rule that is related and compared with previous theoretical work, a continuous version of the population-based incremental learning algorithm, and the generalized mean shift clustering framework. Experimental results are presented that demonstrate the dynamics of the new algorithm on a set of simple test problems.

A general-purpose tunable landscape generator

The research literature on metalieuristic and evolutionary computation has proposed a large number of algorithms for the solution of challenging real-world optimization problems. It is often not possible to study theoretically the performance of these algorithms unless significant assumptions are made on either the algorithm itself or the problems to which it is applied, or both. As a consequence, metalieuristics are typically evaluated empirically using a set of test problems. Unfortunately, relatively little attention has been given to the development of methodologies and tools for the large-scale empirical evaluation and/or comparison of metaheuristics. In this paper, we propose a landscape (test-problem) generator that can be used to generate optimization problem instances for continuous, bound-constrained optimization problems. The landscape generator is parameterized by a small number of parameters, and the values of these parameters have a direct and intuitive interpretation in terms of the geometric features of the landscapes that they produce. An experimental space is defined over algorithms and problems, via a tuple of parameters for any specified algorithm and problem class (here determined by the landscape generator). An experiment is then clearly specified as a point in this space, in a way that is analogous to other areas of experimental algorithmics, and more generally in experimental design. Experimental results are presented, demonstrating the use of the landscape generator. In particular, we analyze some simple, continuous estimation of distribution algorithms, and gain new insights into the behavior of these algorithms using the landscape generator.

Playing in continuous spaces: Some analysis and extension of population-based incremental learning

As an alternative to traditional evolutionary algorithms (EAs), population-based incremental learning (PBIL) maintains a probabilistic model of the best individual(s). Originally, PBIL was applied in binary search spaces. Recently, some work has been done to extend it to continuous spaces. In this paper, we review two such extensions of PBIL. An improved version of the PBIL based on Gaussian model is proposed that combines two main features: a new updating rule that takes into account all the individuals and their fitness values and a self-adaptive learning rate parameter. Furthermore, a new continuous PBIL employing a histogram probabilistic model is proposed. Some experiments results are presented that highlight the features of the new algorithms.

Agent Based Models of Competition and Collaboration

Swarm intelligence is a popular paradigm for algorithm design. Frequently drawing inspiration from natural systems, it assigns simple rules to a set of agents with the aim that, through local interactions, they collectively solve some global problem. Current variants of a popular swarm based optimization algorithm, particle swarm optimization (PSO), are investigated with a focus on premature convergence. A novel variant, dispersive PSO, is proposed to address this problem and is shown to lead to increased robustness and performance compared to current PSO algorithms. A nature inspired decentralised multi-agent algorithm is proposed to solve a constrained problem of distributed task allocation. Agents must collect and process the mail batches, without global knowledge of their environment or communication between agents. New rules for specialisation are proposed and are shown to exhibit improved eciency and exibility compared to existing ones. These new rules are compared with a market based approach to agent control. The eciency (average number of tasks performed), the exibility (ability to react to changes in the environment), and the sensitivity to load (ability to cope with differing demands) are investigated in both static and dynamic environments. A hybrid algorithm combining both approaches, is shown to exhibit improved eciency and robustness. Evolutionary algorithms are employed, both to optimize parameters and to allow the various rules to evolve and compete. We also observe extinction and speciation. In order to interpret algorithm performance we analyse the causes of eciency loss, derive theoretical upper bounds for the eciency, as well as a complete theoretical description of a non-trivial case, and compare these with the experimental results. Motivated by this work we introduce agent "memory" (the possibility for agents to develop preferences for certain cities) and show that not only does it lead to emergent cooperation between agents, but also to a signicant increase in efficiency.

A soft-computing-based method for the automatic discovery of fuzzy rules in databases:uses for academic research and management support in marketing

The study here highlights the potential that analytical methods based on Knowledge Discovery in Databases (KDD) methodologies have to aid both the resolution of unstructured marketing/business problems and the process of scholarly knowledge discovery. The authors present and discuss the application of KDD in these situations prior to the presentation of an analytical method based on fuzzy logic and evolutionary algorithms, developed to analyze marketing databases and uncover relationships among variables. A detailed implementation on a pre-existing data set illustrates the method. © 2012 Published by Elsevier Inc.

What are dynamic optimization problems?

Dynamic Optimization Problems (DOPs) have been widely studied using Evolutionary Algorithms (EAs). Yet, a clear and rigorous definition of DOPs is lacking in the Evolutionary Dynamic Optimization (EDO) community. In this paper, we propose a unified definition of DOPs based on the idea of multiple-decision-making discussed in the Reinforcement Learning (RL) community. We draw a connection between EDO and RL by arguing that both of them are studying DOPs according to our definition of DOPs. We point out that existing EDO or RL research has been mainly focused on some types of DOPs. A conceptualized benchmark problem, which is aimed at the systematic study of various DOPs, is then developed. Some interesting experimental studies on the benchmark reveal that EDO and RL methods are specialized in certain types of DOPs and more importantly new algorithms for DOPs can be developed by combining the strength of both EDO and RL methods.

Distribuição de derivados de petróleo por redes de polidutos: uma abordagem através de algoritmos evolucionários híbridos para um problema triobjetivo

An important problem faced by the oil industry is to distribute multiple oil products through pipelines. Distribution is done in a network composed of refineries (source nodes), storage parks (intermediate nodes), and terminals (demand nodes) interconnected by a set of pipelines transporting oil and derivatives between adjacent areas. Constraints related to storage limits, delivery time, sources availability, sending and receiving limits, among others, must be satisfied. Some researchers deal with this problem under a discrete viewpoint in which the flow in the network is seen as batches sending. Usually, there is no separation device between batches of different products and the losses due to interfaces may be significant. Minimizing delivery time is a typical objective adopted by engineers when scheduling products sending in pipeline networks. However, costs incurred due to losses in interfaces cannot be disregarded. The cost also depends on pumping expenses, which are mostly due to the electricity cost. Since industrial electricity tariff varies over the day, pumping at different time periods have different cost. This work presents an experimental investigation of computational methods designed to deal with the problem of distributing oil derivatives in networks considering three minimization objectives simultaneously: delivery time, losses due to interfaces and electricity cost. The problem is NP-hard and is addressed with hybrid evolutionary algorithms. Hybridizations are mainly focused on Transgenetic Algorithms and classical multi-objective evolutionary algorithm architectures such as MOEA/D, NSGA2 and SPEA2. Three architectures named MOTA/D, NSTA and SPETA are applied to the problem. An experimental study compares the algorithms on thirty test cases. To analyse the results obtained with the algorithms Pareto-compliant quality indicators are used and the significance of the results evaluated with non-parametric statistical tests.

Parallel Problem Solving from Nature – PPSN XIV:14th International Conference, Edinburgh, UK, September 17-21, 2016, Proceedings

This book constitutes the refereed proceedings of the 14th International Conference on Parallel Problem Solving from Nature, PPSN 2016, held in Edinburgh, UK, in September 2016. The total of 93 revised full papers were carefully reviewed and selected from 224 submissions. The meeting began with four workshops which offered an ideal opportunity to explore specific topics in intelligent transportation Workshop, landscape-aware heuristic search, natural computing in scheduling and timetabling, and advances in multi-modal optimization. PPSN XIV also included sixteen free tutorials to give us all the opportunity to learn about new aspects: gray box optimization in theory; theory of evolutionary computation; graph-based and cartesian genetic programming; theory of parallel evolutionary algorithms; promoting diversity in evolutionary optimization: why and how; evolutionary multi-objective optimization; intelligent systems for smart cities; advances on multi-modal optimization; evolutionary computation in cryptography; evolutionary robotics - a practical guide to experiment with real hardware; evolutionary algorithms and hyper-heuristics; a bridge between optimization over manifolds and evolutionary computation; implementing evolutionary algorithms in the cloud; the attainment function approach to performance evaluation in EMO; runtime analysis of evolutionary algorithms: basic introduction; meta-model assisted (evolutionary) optimization. The papers are organized in topical sections on adaption, self-adaption and parameter tuning; differential evolution and swarm intelligence; dynamic, uncertain and constrained environments; genetic programming; multi-objective, many-objective and multi-level optimization; parallel algorithms and hardware issues; real-word applications and modeling; theory; diversity and landscape analysis.

'Artificial Immune Systems: A new Decision Making Paradigm for Operational Research'

Over the last few years, more and more heuristic decision making techniques have been inspired by nature, e.g. evolutionary algorithms, ant colony optimisation and simulated annealing. More recently, a novel computational intelligence technique inspired by immunology has emerged, called Artificial Immune Systems (AIS). This immune system inspired technique has already been useful in solving some computational problems. In this keynote, we will very briefly describe the immune system metaphors that are relevant to AIS. We will then give some illustrative real-world problems suitable for AIS use and show a step-by-step algorithm walkthrough. A comparison of AIS to other well-known algorithms and areas for future work will round this keynote off. It should be noted that as AIS is still a young and evolving field, there is not yet a fixed algorithm template and hence actual implementations might differ somewhat from the examples given here

A New Paradigm for Heuristic Decision Making, Invited Keynote Talk

Over the last few years, more and more heuristic decision making techniques have been inspired by nature, e.g. evolutionary algorithms, ant colony optimisation and simulated annealing. More recently, a novel computational intelligence technique inspired by immunology has emerged, called Artificial Immune Systems (AIS). This immune system inspired technique has already been useful in solving some computational problems. In this keynote, we will very briefly describe the immune system metaphors that are relevant to AIS. We will then give some illustrative real-world problems suitable for AIS use and show a step-by-step algorithm walkthrough. A comparison of AIS to other well-known algorithms and areas for future work will round this keynote off. It should be noted that as AIS is still a young and evolving field, there is not yet a fixed algorithm template and hence actual implementations might differ somewhat from the examples given here.