Un enfoque robusto a un problema de diseño de red multiproducto con incertidumbre en parámetros de entrada

Tesis (Maestro en Ciencias en Ingeniería de Sistemas) U.A.N.L.

Aplicación de algoritmos genéticos en el balanceo de líneas de producción

Tesis (Maestro en Ciencias de la Administración con Especialidad en Producción y Calidad) - U.A.N.L, 2005

Dynamic task allocation and coordination in cooperative multi-agent environments

La coordinació i assignació de tasques en entorns distribuïts ha estat un punt important de la recerca en els últims anys i aquests temes són el cor dels sistemes multi-agent. Els agents en aquests sistemes necessiten cooperar i considerar els altres agents en les seves accions i decisions. A més a més, els agents han de coordinar-se ells mateixos per complir tasques complexes que necessiten més d'un agent per ser complerta. Aquestes tasques poden ser tan complexes que els agents poden no saber la ubicació de les tasques o el temps que resta abans de que les tasques quedin obsoletes. Els agents poden necessitar utilitzar la comunicació amb l'objectiu de conèixer la tasca en l'entorn, en cas contrari, poden perdre molt de temps per trobar la tasca dins de l'escenari. De forma similar, el procés de presa de decisions distribuït pot ser encara més complexa si l'entorn és dinàmic, amb incertesa i en temps real. En aquesta dissertació, considerem entorns amb sistemes multi-agent amb restriccions i cooperatius (dinàmics, amb incertesa i en temps real). En aquest sentit es proposen dues aproximacions que permeten la coordinació dels agents. La primera és un mecanisme semi-centralitzat basat en tècniques de subhastes combinatòries i la idea principal es minimitzar el cost de les tasques assignades des de l'agent central cap als equips d'agents. Aquest algoritme té en compte les preferències dels agents sobre les tasques. Aquestes preferències estan incloses en el bid enviat per l'agent. La segona és un aproximació d'scheduling totalment descentralitzat. Això permet als agents assignar les seves tasques tenint en compte les preferències temporals sobre les tasques dels agents. En aquest cas, el rendiment del sistema no només depèn de la maximització o del criteri d'optimització, sinó que també depèn de la capacitat dels agents per adaptar les seves assignacions eficientment. Addicionalment, en un entorn dinàmic, els errors d'execució poden succeir a qualsevol pla degut a la incertesa i error de accions individuals. A més, una part indispensable d'un sistema de planificació és la capacitat de re-planificar. Aquesta dissertació també proveeix una aproximació amb re-planificació amb l'objectiu de permetre als agent re-coordinar els seus plans quan els problemes en l'entorn no permeti la execució del pla. Totes aquestes aproximacions s'han portat a terme per permetre als agents assignar i coordinar de forma eficient totes les tasques complexes en un entorn multi-agent cooperatiu, dinàmic i amb incertesa. Totes aquestes aproximacions han demostrat la seva eficiència en experiments duts a terme en l'entorn de simulació RoboCup Rescue.

Characterisation of the operation & maintenance phase in PV rural electrification programmes

Con 1.300 millones de personas en el mundo sin acceso a la electricidad (la mayoría en entornos rurales de países empobrecidos), la energía solar fotovoltaica constituye una solución viable técnica y económicamente para electrificar las zonas más remotas del planeta donde las redes eléctricas convencionales no llegan. Casi todos los países en el mundo han desarrollado algún tipo de programa de electrificación fotovoltaica rural durante los últimos 40 años, principalmente los países más pobres, donde a través de diferentes modelos de financiación, se han instalado millones de sistemas solares domiciliarios (pequeños sistemas fotovoltaicos para uso doméstico). Durante este largo período, se han ido superando muchas barreras, como la mejora de la calidad de los sistemas fotovoltaicos, la reducción de costes, la optimización del diseño y del dimensionado de los sistemas, la disponibilidad financiera para implantar programas de electrificación rural, etc. Gracias a esto, la electrificación rural descentralizada ha experimentado recientemente un salto de escala caracterizada por la implantación de grandes programas con miles de sistemas solares domiciliarios e integrando largos períodos de mantenimiento. Muchos de estos grandes programas se están llevando a cabo con limitado éxito, ya que generalmente parten de supuestos e hipótesis poco contrastadas con la realidad, comprometiendo así un retorno económico que permita el desarrollo de esta actividad a largo plazo. En este escenario surge un nuevo reto: el de cómo garantizar la sostenibilidad de los grandes programas de electrificación rural fotovoltaica. Se argumenta que la principal causa de esta falta de rentabilidad es el imprevisto alto coste de la fase de operación y mantenimiento. Cuestiones clave tales como la estructura de costes de operación y mantenimiento o la fiabilidad de los componentes del sistema fotovoltaico no están bien caracterizados hoy en día. Esta situación limita la capacidad de diseñar estructuras de mantenimiento capaces de asegurar la sostenibilidad y la rentabilidad del servicio de operación y mantenimiento en estos programas. Esta tesis doctoral tiene como objetivo responder a estas cuestiones. Se ha realizado varios estudios sobre la base de un gran programa de electrificación rural fotovoltaica real llevado a cabo en Marruecos con más de 13.000 sistemas solares domiciliarios instalados. Sobre la base de este programa se ha hecho una evaluación en profundidad de la fiabilidad de los sistemas solares a partir de los datos de mantenimiento recogidos durante 5 años con más de 80.000 inputs. Los resultados han permitido establecer las funciones de fiabilidad de los equipos tal y como se comportan en condiciones reales de operación, las tasas de fallos y los tiempos medios hasta el fallo para los principales componentes del sistema, siendo este el primer caso de divulgación de resultados de este tipo en el campo de la electrificación rural fotovoltaica. Los dos principales componentes del sistema solar domiciliario, la batería y el módulo fotovoltaico, han sido analizados en campo a través de una muestra de 41 sistemas trabajando en condiciones reales pertenecientes al programa solar marroquí. Por un lado se ha estudiado la degradación de la capacidad de las baterías y por otro la degradación de potencia de los módulos fotovoltaicos. En el caso de las baterías, los resultados nos han permitido caracterizar la curva de degradación en capacidad llegando a obtener una propuesta de nueva definición del umbral de vida útil de las baterías en electrificación rural. También sobre la base del programa solar de Marruecos se ha llevado a cabo un estudio de caracterización de los costes reales de operación y mantenimiento a partir de la base de datos de contabilidad del programa registrados durante 5 años. Los resultados del estudio han permitido definir cuáles son costes que más incidencia tienen en el coste global. Se han obtenido los costes unitarios por sistema instalado y se han calculado los montantes de las cuotas de mantenimiento de los usuarios para garantizar la rentabilidad de la operación y mantenimiento. Finalmente, se propone un modelo de optimización matemática para diseñar estructuras de mantenimiento basado en los resultados de los estudios anteriores. La herramienta, elaborada mediante programación lineal entera mixta, se ha aplicado al programa marroquí con el fin de validar el modelo propuesto. ABSTRACT With 1,300 million people worldwide deprived of access to electricity (mostly in rural environments), photovoltaic solar energy has proven to be a cost‐effective solution and the only hope for electrifying the most remote inhabitants of the planet, where conventional electric grids do not reach because they are unaffordable. Almost all countries in the world have had some kind of rural photovoltaic electrification programme during the past 40 years, mainly the poorer countries, where through different organizational models, millions of solar home systems (small photovoltaic systems for domestic use) have been installed. During this long period, many barriers have been overcome, such as quality enhancement, cost reduction, the optimization of designing and sizing, financial availability, etc. Thanks to this, decentralized rural electrification has recently experienced a change of scale characterized by new programmes with thousands of solar home systems and long maintenance periods. Many of these large programmes are being developed with limited success, as they have generally been based on assumptions that do not correspond to reality, compromising the economic return that allows long term activity. In this scenario a new challenge emerges, which approaches the sustainability of large programmes. It is argued that the main cause of unprofitability is the unexpected high cost of the operation and maintenance of the solar systems. In fact, the lack of a paradigm in decentralized rural services has led to many private companies to carry out decentralized electrification programmes blindly. Issues such as the operation and maintenance cost structure or the reliability of the solar home system components have still not been characterized. This situation does not allow optimized maintenance structure to be designed to assure the sustainability and profitability of the operation and maintenance service. This PhD thesis aims to respond to these needs. Several studies have been carried out based on a real and large photovoltaic rural electrification programme carried out in Morocco with more than 13,000 solar home systems. An in‐depth reliability assessment has been made from a 5‐year maintenance database with more than 80,000 maintenance inputs. The results have allowed us to establish the real reliability functions, the failure rate and the main time to failure of the main components of the system, reporting these findings for the first time in the field of rural electrification. Both in‐field experiments on the capacity degradation of batteries and power degradation of photovoltaic modules have been carried out. During the experiments both samples of batteries and modules were operating under real conditions integrated into the solar home systems of the Moroccan programme. In the case of the batteries, the results have enabled us to obtain a proposal of definition of death of batteries in rural electrification. A cost assessment of the Moroccan experience based on a 5‐year accounting database has been carried out to characterize the cost structure of the programme. The results have allowed the major costs of the photovoltaic electrification to be defined. The overall cost ratio per installed system has been calculated together with the necessary fees that users would have to pay to make the operation and maintenance affordable. Finally, a mathematical optimization model has been proposed to design maintenance structures based on the previous study results. The tool has been applied to the Moroccan programme with the aim of validating the model.

Coupled CFD Shape Optimization for aerodynamic profiles

The present document deals with the optimization of shape of aerodynamic profiles -- The objective is to reduce the drag coefficient on a given profile without penalising the lift coefficient -- A set of control points defining the geometry are passed and parameterized as a B-Spline curve -- These points are modified automatically by means of CFD analysis -- A given shape is defined by an user and a valid volumetric CFD domain is constructed from this planar data and a set of user-defined parameters -- The construction process involves the usage of 2D and 3D meshing algorithms that were coupled into own- code -- The volume of air surrounding the airfoil and mesh quality are also parametrically defined -- Some standard NACA profiles were used by obtaining first its control points in order to test the algorithm -- Navier-Stokes equations were solved for turbulent, steady-state ow of compressible uids using the k-epsilon model and SIMPLE algorithm -- In order to obtain data for the optimization process an utility to extract drag and lift data from the CFD simulation was added -- After a simulation is run drag and lift data are passed to the optimization process -- A gradient-based method using the steepest descent was implemented in order to define the magnitude and direction of the displacement of each control point -- The control points and other parameters defined as the design variables are iteratively modified in order to achieve an optimum -- Preliminary results on conceptual examples show a decrease in drag and a change in geometry that obeys to aerodynamic behavior principles

Designing Efficient Subsidy Policies in a Regional Economy: A Multicriteria Decision-Making (MCDM)-Computable General Equilibrium (CGE) Approach

Since policy-makers usually pursue several conflicting objectives, policy-making can be understood as a multicriteria decision problem. Following the methodological proposal by André and Cardenete (2005) André, F. J. and Cardenete, M. A. 2005. Multicriteria Policy Making. Defining Efficient Policies in a General Equilibrium Model, Seville: Centro de Estudios Andaluces. Working Paper No. E2005/04, multi-objective programming is used in connection with a computable general equilibrium model to represent optimal policy-making and to obtain so-called efficient policies in an application to a regional economy (Andalusia, Spain). This approach is applied to the design of subsidy policies under two different scenarios. In the first scenario, it is assumed that the government is concerned just about two objectives: ensuring the profitability of a key strategic sector and increasing overall output. Finally, the scope of the exercise is enlarged by solving a problem with seven policy objectives, including both general and sectorial objectives. It is concluded that the observed policy could have been Pareto-improved in several directions.

Intertemporal and spatial location of disposal facilities

The optimal capacities and locations of a sequence of landfills are studied, and the interactions between these characteristics are considered. Deciding the capacity of a landfill has some spatial implications since it affects the feasible region for the remaining landfills, and some temporal implications because the capacity determines the lifetime of the landfill and hence the moment of time when the next landfills should be constructed. Some general mathematical properties of the solution are provided and interpreted from an economic point of view. The resulting problem turns out to be non-convex and, therefore, it cannot be solved by conventional optimization techniques. Some global optimization methods are used to solve the problem in a particular case in order to illustrate how the solution depends on the parameter values.

A New Multi-Objective Approach for Molecular Docking Based on RMSD and Binding Energy

Ligand-protein docking is an optimization problem based on predicting the position of a ligand with the lowest binding energy in the active site of the receptor. Molecular docking problems are traditionally tackled with single-objective, as well as with multi-objective approaches, to minimize the binding energy. In this paper, we propose a novel multi-objective formulation that considers: the Root Mean Square Deviation (RMSD) difference in the coordinates of ligands and the binding (intermolecular) energy, as two objectives to evaluate the quality of the ligand-protein interactions. To determine the kind of Pareto front approximations that can be obtained, we have selected a set of representative multi-objective algorithms such as NSGA-II, SMPSO, GDE3, and MOEA/D. Their performances have been assessed by applying two main quality indicators intended to measure convergence and diversity of the fronts. In addition, a comparison with LGA, a reference single-objective evolutionary algorithm for molecular docking (AutoDock) is carried out. In general, SMPSO shows the best overall results in terms of energy and RMSD (value lower than 2A for successful docking results). This new multi-objective approach shows an improvement over the ligand-protein docking predictions that could be promising in in silico docking studies to select new anticancer compounds for therapeutic targets that are multidrug resistant.

Robust solutions of bi-blend recipe optimization with quadratic constraints

Production companies use raw materials to compose end-products. They often make different products with the same raw materials. In this research, the focus lies on the production of two end-products consisting of (partly) the same raw materials as cheap as possible. Each of the products has its own demand and quality requirements consisting of quadratic constraints. The minimization of the costs, given the quadratic constraints is a global optimization problem, which can be difficult because of possible local optima. Therefore, the multi modal character of the (bi-) blend problem is investigated. Standard optimization packages (solvers) in Matlab and GAMS were tested on their ability to solve the problem. In total 20 test cases were generated and taken from literature to test solvers on their effectiveness and efficiency to solve the problem. The research also gives insight in adjusting the quadratic constraints of the problem in order to make a robust problem formulation of the bi-blend problem.

Robustness in facility location

Facility location concerns the placement of facilities, for various objectives, by use of mathematical models and solution procedures. Almost all facility location models that can be found in literature are based on minimizing costs or maximizing cover, to cover as much demand as possible. These models are quite efficient for finding an optimal location for a new facility for a particular data set, which is considered to be constant and known in advance. In a real world situation, input data like demand and travelling costs are not fixed, nor known in advance. This uncertainty and uncontrollability can lead to unacceptable losses or even bankruptcy. A way of dealing with these factors is robustness modelling. A robust facility location model aims to locate a facility that stays within predefined limits for all expectable circumstances as good as possible. The deviation robustness concept is used as basis to develop a new competitive deviation robustness model. The competition is modelled with a Huff based model, which calculates the market share of the new facility. Robustness in this model is defined as the ability of a facility location to capture a minimum market share, despite variations in demand. A test case is developed by which algorithms can be tested on their ability to solve robust facility location models. Four stochastic optimization algorithms are considered from which Simulated Annealing turned out to be the most appropriate. The test case is slightly modified for a competitive market situation. With the Simulated Annealing algorithm, the developed competitive deviation model is solved, for three considered norms of deviation. At the end, also a grid search is performed to illustrate the landscape of the objective function of the competitive deviation model. The model appears to be multimodal and seems to be challenging for further research.

On multimodality of obnoxious faclity location models

Obnoxious single facility location models are models that have the aim to find the best location for an undesired facility. Undesired is usually expressed in relation to the so-called demand points that represent locations hindered by the facility. Because obnoxious facility location models as a rule are multimodal, the standard techniques of convex analysis used for locating desirable facilities in the plane may be trapped in local optima instead of the desired global optimum. It is assumed that having more optima coincides with being harder to solve. In this thesis the multimodality of obnoxious single facility location models is investigated in order to know which models are challenging problems in facility location problems and which are suitable for site selection. Selected for this are the obnoxious facility models that appear to be most important in literature. These are the maximin model, that maximizes the minimum distance from demand point to the obnoxious facility, the maxisum model, that maximizes the sum of distance from the demand points to the facility and the minisum model, that minimizes the sum of damage of the facility to the demand points. All models are measured with the Euclidean distances and some models also with the rectilinear distance metric. Furthermore a suitable algorithm is selected for testing multimodality. Of the tested algorithms in this thesis, Multistart is most appropriate. A small numerical experiment shows that Maximin models have on average the most optima, of which the model locating an obnoxious linesegment has the most. Maximin models have few optima and are thus not very hard to solve. From the Minisum models, the models that have the most optima are models that take wind into account. In general can be said that the generic models have less optima than the weighted versions. Models that are measured with the rectilinear norm do have more solutions than the same models measured with the Euclidean norm. This can be explained for the maximin models in the numerical example because the shape of the norm coincides with a bound of the feasible area, so not all solutions are different optima. The difference found in number of optima of the Maxisum and Minisum can not be explained by this phenomenon.

Dynamic Multi-Objective Optimization With jMetal and Spark: a Case Study

Technologies for Big Data and Data Science are receiving increasing research interest nowadays. This paper introduces the prototyping architecture of a tool aimed to solve Big Data Optimization problems. Our tool combines the jMetal framework for multi-objective optimization with Apache Spark, a technology that is gaining momentum. In particular, we make use of the streaming facilities of Spark to feed an optimization problem with data from different sources. We demonstrate the use of our tool by solving a dynamic bi-objective instance of the Traveling Salesman Problem (TSP) based on near real-time traffic data from New York City, which is updated several times per minute. Our experiment shows that both jMetal and Spark can be integrated providing a software platform to deal with dynamic multi-optimization problems.

Optimización de parámetros y modelación matemática del proceso de soldadura por láser de disco de diodos YB:YAG, aplicado en aceros avanzados AHSS

La aplicación del uso de la tecnología láser para la unión de materiales se ha incrementado sustancialmente en la industria metal-mecánica, esto se atribuye principalmente a las diferentes ventajas que tiene este proceso sobre los procesos de soldadura convencionales, como son la reducción en el costo de procesamiento, aumento de la productividad, incremento de la calidad del producto, la reducción de las zonas afectadas por el calor, la reducción de la distorsión en la piezas soldadas y además la versatilidad que representa la soldadura láser por ser un proceso sin contacto. No obstante el uso del láser para la unión de materiales en México se considera todavía una tecnología emergente, son muy pocas las industrias que han migrado de los procesos de soldadura convencionales al proceso de unión de materiales por rayo láser. Una de las industrias que ha empezado a utilizar el proceso de soldadura por láser en México, es la automotriz, en la cual constantemente se está buscado evitar un rezago tecnológico en los procesos de conformado y soldadura de piezas metálicas. Sin embargo en la actualidad, en la industria automotriz mexicana existe una gran dependencia de expertos de otros países para la supervisión, atención y el control de los procesos avanzados, como lo es el de la soldadura láser.En este trabajo, para lograr una mayor comprensión del proceso y del efecto de sus variables, se propuso aplicar una metodología de optimización en dos casos de estudio, en los cuales se utilizó una configuración de unión de soldadura a traslape con el modo de soldadura de ojo de cerradura o penetración completa, que es más bien conocida como “Keyhole welding”.

Optimización dinámica con información híbrida: dos casos prácticos

[ES] La programación dinámica es un método de optimización de sistemas o de su representación matemática, donde se opera por fases, es decir, las decisiones se toman en forma secuencial.

El modelado en Cabri de la función cuadrática como estrategia de verificación y generalización en la solución de un problema de optimización

Este articulo reporta el trabajo de estudiantes de noveno a undécimo grado en la solución de un problema de optimización, en donde el modelado juega un papel principal puesto que les permitió llegar a conclusiones y generalizaciones que no fueron posibles a través del lápiz y el papel. Se comentan las estrategias y procedimientos que siguieron los estudiantes y se destaca la importancia de la mediación instrumental a través de la modelación en el proceso de verificación de la solución del problema.