13 research outputs found

    A hybrid modified-NSGA-II VNS algorithm for the Multi-Objective Critical Disruption Path Problem

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    This paper considers a Multiple Objective variant of the Critical Disruption Path problem to extend its suitability in a range of security operations relying on path-based network interdiction, including flight pattern optimisation for surveillance. Given a pair of nodes s and t from the network to be monitored, the problem seeks for loopless s - t paths such that, within the induced subgraph obtained via deletion of the path, the size of the largest connected component is minimised, the number of connected components is maximised, while concurrently reducing as much as possible the cost of such disruption path. These three objectives are possibly in conflict with each other, and the scope of this work is to allow for an efficient and insightful approximation of the Pareto front, looking for a trade-off between costs and effectiveness to secure the most convenient paths for security and surveillance operations. We first introduce and formulate the Multi-Objective Critical Disruption Path Problem (Multi-Objs-CDP) as a mixed integer programming formulation (MO-CDP), then we propose an original evolutionary metaheuristic algorithm hybridising modified-NSGA-II and VNS for finding an approximation of the Pareto front, as well as a procedure securing the efficient generation of a high quality pool of initial solutions. The experimental performance of the proposed algorithm, as compared with a variety of competing approaches, proves to be fully satisfactory in terms of time efficiency and quality of the solutions obtained on a set of medium to large benchmark instances

    Advanced and Innovative Optimization Techniques in Controllers: A Comprehensive Review

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    New commercial power electronic controllers come to the market almost every day to help improve electronic circuit and system performance and efficiency. In DC–DC switching-mode converters, a simple and elegant hysteretic controller is used to regulate the basic buck, boost and buck–boost converters under slightly different configurations. In AC–DC converters, the input current shaping for power factor correction posts a constraint. But, several brilliant commercial controllers are demonstrated for boost and fly back converters to achieve almost perfect power factor correction. In this paper a comprehensive review of the various advanced optimization techniques used in power electronic controllers is presented

    Exact and non-exact procedures for solving the response time variability problem (RTVP)

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    Premi extraordinari doctorat curs 2009-2010, àmbit d’Enginyeria IndustrialCuando se ha de compartir un recurso entre demandas (de productos, clientes, tareas, etc.) competitivas que requieren una atención regular, es importante programar el derecho al acceso del recurso de alguna forma justa de manera que cada producto, cliente o tarea reciba un acceso al recurso proporcional a su demanda relativa al total de las demandas competitivas. Este tipo de problemas de secuenciación pueden ser generalizados bajo el siguiente esquema. Dados n símbolos, cada uno con demanda di (i = 1,...,n), se ha de generar una secuencia justa o regular donde cada símbolo aparezca di veces. No existe una definición universal de justicia, ya que puede haber varias métricas razonables para medirla según el problema específico considerado. En el Problema de Variabilidad en el Tiempo de Respuesta, o Response Time Variability Problem (RTVP) en inglés, la injusticia o irregularidad de una secuencia es medida como la suma, para todos los símbolos, de sus variabilidades en las distancias en que las copias de cada símbolo son secuenciados. Así, el objetivo del RTVP es encontrar la secuencia que minimice la variabilidad total. En otras palabras, el objetivo del RTVP es minimizar la variabilidad de los instantes en que los productos, clientes o trabajos reciben el recurso necesario. Este problema aparece en una amplia variedad de situaciones de la vida real; entre otras, secuenciación en líneas de modelo-mixto bajo just-in-time (JIT), en asignación de recursos en sistemas computacionales multi-hilo como sistemas operativos, servidores de red y aplicaciones mutimedia, en el mantenimiento periódico de maquinaria, en la recolección de basura, en la programación de comerciales en televisión y en el diseño de rutas para agentes comerciales con múltiples visitas a un mismo cliente. En algunos de estos problemas la regularidad no es una propiedad deseable por sí misma, si no que ayuda a minimizar costes. De hecho, cuando los costes son proporcionales al cuadrado de las distancias, el problema de minimizar costes y el RTVP son equivalentes. El RTVP es muy difícil de resolver (se ha demostrado que es NP-hard). El tamaño de las instancias del RTVP que pueden ser resueltas óptimamente con el mejor método exacto existente en la literatura tiene un límite práctico de 40 unidades. Por otro lado, los métodos no exactos propuestos en la literatura para resolver instancias mayores consisten en heurísticos simples que obtienen soluciones rápidamente, pero cuya calidad puede ser mejorada. Por tanto, los métodos de resolución existentes en la literatura son insuficientes. El principal objetivo de esta tesis es mejorar la resolución del RTVP. Este objetivo se divide en los dos siguientes subobjetivos : 1) aumentar el tamaño de las instancias del RTVP que puedan ser resueltas de forma óptima en un tiempo de computación práctico, y 2) obtener de forma eficiente soluciones lo más cercanas a las óptimas para instancias mayores. Además, la tesis tiene los dos siguientes objetivos secundarios: a) investigar el uso de metaheurísticos bajo el esquema de los hiper-heurísticos, y b) diseñar un procedimiento sistemático y automático para fijar los valores adecuados a los parámetros de los algoritmos. Se han desarrollado diversos métodos para alcanzar los objetivos anteriormente descritos. Para la resolución del RTVP se ha diseñado un método exacto basado en la técnica branch and bound y el tamaño de las instancias que pueden resolverse en un tiempo práctico se ha incrementado a 55 unidades. Para instancias mayores, se han diseñado métodos heurísticos, metaheurísticos e hiper-heurísticos, los cuales pueden obtener soluciones óptimas o casi óptimas rápidamente. Además, se ha propuesto un procedimiento sistemático y automático para tunear parámetros que aprovecha las ventajas de dos procedimientos existentes (el algoritmo Nelder & Mead y CALIBRA).When a resource must be shared between competing demands (of products, clients, jobs, etc.) that require regular attention, it is important to schedule the access right to the resource in some fair manner so that each product, client or job receives a share of the resource that is proportional to its demand relative to the total of the competing demands. These types of sequencing problems can be generalized under the following scheme. Given n symbols, each one with demand di (i = 1,...,n), a fair or regular sequence must be built in which each symbol appears di times. There is not a universal definition of fairness, as several reasonable metrics to measure it can be defined according to the specific considered problem. In the Response Time Variability Problem (RTVP), the unfairness or the irregularity of a sequence is measured by the sum, for all symbols, of their variabilities in the positions at which the copies of each symbol are sequenced. Thus, the objective of the RTVP is to find the sequence that minimises the total variability. In other words, the RTVP objective is to minimise the variability in the instants at which products, clients or jobs receive the necessary resource. This problem appears in a broad range of real-world areas. Applications include sequencing of mixed-model assembly lines under just-in-time (JIT), resource allocation in computer multi-threaded systems such as operating systems, network servers and media-based applications, periodic machine maintenance, waste collection, scheduling commercial videotapes for television and designing of salespeople's routes with multiple visits, among others. In some of these problems the regularity is not a property desirable by itself, but it helps to minimise costs. In fact, when the costs are proportional to the square of the distances, the problem of minimising costs and the RTVP are equivalent. The RTVP is very hard to be solved (it has been demonstrated that it is NP-hard). The size of the RTVP instances that can be solved optimally with the best exact method existing in the literature has a practical limit of 40 units. On the other hand, the non-exact methods proposed in the literature to solve larger instances are simple heuristics that obtains solutions quickly, but the quality of the obtained solutions can be improved. Thus, the solution methods existing in the literature are not enough to solve the RTVP. The main objective of this thesis is to improve the resolution of the RTVP. This objective is split in the two following sub-objectives: 1) to increase the size of the RTVP instances that can be solved optimally in a practical computing time; and 2) to obtain efficiently near-optimal solutions for larger instances. Moreover, the thesis has the following two secondary objectives: a) to research the use of metaheuristics under the scheme of hyper-heuristics, and b) to design a systematic, hands-off procedure to set the suitable values of the algorithm parameters. To achieve the aforementioned objectives, several procedures have been developed. To solve the RTVP an exact procedure based on the branch and bound technique has been designed and the size of the instances that can be solved in a practical time has been increased to 55 units. For larger instances, heuristic, heuristic, metaheuristic and hyper-heuristic procedures have been designed, which can obtain optimal or near-optimal solutions quickly. Moreover, a systematic, hands-off fine-tuning method that takes advantage of the two existing ones (Nelder & Mead algorithm and CALIBRA) has been proposed.Award-winningPostprint (published version

    Proceedings of the XIII Global Optimization Workshop: GOW'16

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    [Excerpt] Preface: Past Global Optimization Workshop shave been held in Sopron (1985 and 1990), Szeged (WGO, 1995), Florence (GO’99, 1999), Hanmer Springs (Let’s GO, 2001), Santorini (Frontiers in GO, 2003), San José (Go’05, 2005), Mykonos (AGO’07, 2007), Skukuza (SAGO’08, 2008), Toulouse (TOGO’10, 2010), Natal (NAGO’12, 2012) and Málaga (MAGO’14, 2014) with the aim of stimulating discussion between senior and junior researchers on the topic of Global Optimization. In 2016, the XIII Global Optimization Workshop (GOW’16) takes place in Braga and is organized by three researchers from the University of Minho. Two of them belong to the Systems Engineering and Operational Research Group from the Algoritmi Research Centre and the other to the Statistics, Applied Probability and Operational Research Group from the Centre of Mathematics. The event received more than 50 submissions from 15 countries from Europe, South America and North America. We want to express our gratitude to the invited speaker Panos Pardalos for accepting the invitation and sharing his expertise, helping us to meet the workshop objectives. GOW’16 would not have been possible without the valuable contribution from the authors and the International Scientific Committee members. We thank you all. This proceedings book intends to present an overview of the topics that will be addressed in the workshop with the goal of contributing to interesting and fruitful discussions between the authors and participants. After the event, high quality papers can be submitted to a special issue of the Journal of Global Optimization dedicated to the workshop. [...

    Exact and non-exact procedures for solving the response time variability problem (RTVP)

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    Cuando se ha de compartir un recurso entre demandas (de productos, clientes, tareas, etc.) competitivas que requieren una atención regular, es importante programar el derecho al acceso del recurso de alguna forma justa de manera que cada producto, cliente o tarea reciba un acceso al recurso proporcional a su demanda relativa al total de las demandas competitivas. Este tipo de problemas de secuenciación pueden ser generalizados bajo el siguiente esquema. Dados n símbolos, cada uno con demanda di (i = 1,...,n), se ha de generar una secuencia justa o regular donde cada símbolo aparezca di veces. No existe una definición universal de justicia, ya que puede haber varias métricas razonables para medirla según el problema específico considerado. En el Problema de Variabilidad en el Tiempo de Respuesta, o Response Time Variability Problem (RTVP) en inglés, la injusticia o irregularidad de una secuencia es medida como la suma, para todos los símbolos, de sus variabilidades en las distancias en que las copias de cada símbolo son secuenciados. Así, el objetivo del RTVP es encontrar la secuencia que minimice la variabilidad total. En otras palabras, el objetivo del RTVP es minimizar la variabilidad de los instantes en que los productos, clientes o trabajos reciben el recurso necesario. Este problema aparece en una amplia variedad de situaciones de la vida real; entre otras, secuenciación en líneas de modelo-mixto bajo just-in-time (JIT), en asignación de recursos en sistemas computacionales multi-hilo como sistemas operativos, servidores de red y aplicaciones mutimedia, en el mantenimiento periódico de maquinaria, en la recolección de basura, en la programación de comerciales en televisión y en el diseño de rutas para agentes comerciales con múltiples visitas a un mismo cliente. En algunos de estos problemas la regularidad no es una propiedad deseable por sí misma, si no que ayuda a minimizar costes. De hecho, cuando los costes son proporcionales al cuadrado de las distancias, el problema de minimizar costes y el RTVP son equivalentes. El RTVP es muy difícil de resolver (se ha demostrado que es NP-hard). El tamaño de las instancias del RTVP que pueden ser resueltas óptimamente con el mejor método exacto existente en la literatura tiene un límite práctico de 40 unidades. Por otro lado, los métodos no exactos propuestos en la literatura para resolver instancias mayores consisten en heurísticos simples que obtienen soluciones rápidamente, pero cuya calidad puede ser mejorada. Por tanto, los métodos de resolución existentes en la literatura son insuficientes. El principal objetivo de esta tesis es mejorar la resolución del RTVP. Este objetivo se divide en los dos siguientes subobjetivos : 1) aumentar el tamaño de las instancias del RTVP que puedan ser resueltas de forma óptima en un tiempo de computación práctico, y 2) obtener de forma eficiente soluciones lo más cercanas a las óptimas para instancias mayores. Además, la tesis tiene los dos siguientes objetivos secundarios: a) investigar el uso de metaheurísticos bajo el esquema de los hiper-heurísticos, y b) diseñar un procedimiento sistemático y automático para fijar los valores adecuados a los parámetros de los algoritmos. Se han desarrollado diversos métodos para alcanzar los objetivos anteriormente descritos. Para la resolución del RTVP se ha diseñado un método exacto basado en la técnica branch and bound y el tamaño de las instancias que pueden resolverse en un tiempo práctico se ha incrementado a 55 unidades. Para instancias mayores, se han diseñado métodos heurísticos, metaheurísticos e hiper-heurísticos, los cuales pueden obtener soluciones óptimas o casi óptimas rápidamente. Además, se ha propuesto un procedimiento sistemático y automático para tunear parámetros que aprovecha las ventajas de dos procedimientos existentes (el algoritmo Nelder & Mead y CALIBRA).When a resource must be shared between competing demands (of products, clients, jobs, etc.) that require regular attention, it is important to schedule the access right to the resource in some fair manner so that each product, client or job receives a share of the resource that is proportional to its demand relative to the total of the competing demands. These types of sequencing problems can be generalized under the following scheme. Given n symbols, each one with demand di (i = 1,...,n), a fair or regular sequence must be built in which each symbol appears di times. There is not a universal definition of fairness, as several reasonable metrics to measure it can be defined according to the specific considered problem. In the Response Time Variability Problem (RTVP), the unfairness or the irregularity of a sequence is measured by the sum, for all symbols, of their variabilities in the positions at which the copies of each symbol are sequenced. Thus, the objective of the RTVP is to find the sequence that minimises the total variability. In other words, the RTVP objective is to minimise the variability in the instants at which products, clients or jobs receive the necessary resource. This problem appears in a broad range of real-world areas. Applications include sequencing of mixed-model assembly lines under just-in-time (JIT), resource allocation in computer multi-threaded systems such as operating systems, network servers and media-based applications, periodic machine maintenance, waste collection, scheduling commercial videotapes for television and designing of salespeople's routes with multiple visits, among others. In some of these problems the regularity is not a property desirable by itself, but it helps to minimise costs. In fact, when the costs are proportional to the square of the distances, the problem of minimising costs and the RTVP are equivalent. The RTVP is very hard to be solved (it has been demonstrated that it is NP-hard). The size of the RTVP instances that can be solved optimally with the best exact method existing in the literature has a practical limit of 40 units. On the other hand, the non-exact methods proposed in the literature to solve larger instances are simple heuristics that obtains solutions quickly, but the quality of the obtained solutions can be improved. Thus, the solution methods existing in the literature are not enough to solve the RTVP. The main objective of this thesis is to improve the resolution of the RTVP. This objective is split in the two following sub-objectives: 1) to increase the size of the RTVP instances that can be solved optimally in a practical computing time; and 2) to obtain efficiently near-optimal solutions for larger instances. Moreover, the thesis has the following two secondary objectives: a) to research the use of metaheuristics under the scheme of hyper-heuristics, and b) to design a systematic, hands-off procedure to set the suitable values of the algorithm parameters. To achieve the aforementioned objectives, several procedures have been developed. To solve the RTVP an exact procedure based on the branch and bound technique has been designed and the size of the instances that can be solved in a practical time has been increased to 55 units. For larger instances, heuristic, heuristic, metaheuristic and hyper-heuristic procedures have been designed, which can obtain optimal or near-optimal solutions quickly. Moreover, a systematic, hands-off fine-tuning method that takes advantage of the two existing ones (Nelder & Mead algorithm and CALIBRA) has been proposed

    Data science, analytics and artificial intelligence in e-health : trends, applications and challenges

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    Acknowledgments. This work has been partially supported by the Divina Pastora Seguros company.More than ever, healthcare systems can use data, predictive models, and intelligent algorithms to optimize their operations and the service they provide. This paper reviews the existing literature regarding the use of data science/analytics methods and artificial intelligence algorithms in healthcare. The paper also discusses how healthcare organizations can benefit from these tools to efficiently deal with a myriad of new possibilities and strategies. Examples of real applications are discussed to illustrate the potential of these methods. Finally, the paper highlights the main challenges regarding the use of these methods in healthcare, as well as some open research lines

    Air Force Institute of Technology Research Report 2004

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    This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, and Engineering Physics

    Fuelling the zero-emissions road freight of the future: routing of mobile fuellers

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    The future of zero-emissions road freight is closely tied to the sufficient availability of new and clean fuel options such as electricity and Hydrogen. In goods distribution using Electric Commercial Vehicles (ECVs) and Hydrogen Fuel Cell Vehicles (HFCVs) a major challenge in the transition period would pertain to their limited autonomy and scarce and unevenly distributed refuelling stations. One viable solution to facilitate and speed up the adoption of ECVs/HFCVs by logistics, however, is to get the fuel to the point where it is needed (instead of diverting the route of delivery vehicles to refuelling stations) using "Mobile Fuellers (MFs)". These are mobile battery swapping/recharging vans or mobile Hydrogen fuellers that can travel to a running ECV/HFCV to provide the fuel they require to complete their delivery routes at a rendezvous time and space. In this presentation, new vehicle routing models will be presented for a third party company that provides MF services. In the proposed problem variant, the MF provider company receives routing plans of multiple customer companies and has to design routes for a fleet of capacitated MFs that have to synchronise their routes with the running vehicles to deliver the required amount of fuel on-the-fly. This presentation will discuss and compare several mathematical models based on different business models and collaborative logistics scenarios
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