This thesis presents two new routing problems, both with objective functions focused on relative positioning of teams during the routing horizon. The relative positioning results in temporal and spatial dependencies among routes and is quantified with a nonlinear dispersion metric, designed to evaluate the instantaneous distances among teams over a time interval. This metric allows the design of objective functions to approximate teams during routes execution, when minimized, or disperse them, when maximized. Both approximation and dispersion are important routing characteristics in some practical applications, and two new optimization problems are proposed with these opposite objectives. The first one is a variation of the Multiple Traveling Salesman Problem, and its goal is to find a set of tours where the salesmen travel close to each other, minimizing dispersion. A Local Search Genetic Algorithm is proposed to solve the problem. It includes specialized genetic operators and neighborhoods. A new set of benchmark instances is proposed, adapted for the new problem from literature instances. Computational results show that the proposed approach provides solutions with the desired characteristics of minimal dispersion. The second problem is a bi-objective arc routing problem in which routes must be constructed in order to maximize collected profit and dispersion of teams. The maximization of the dispersion metric fosters the scattering of the teams during routing procedure. Usually, profit and dispersion objectives are conflicting, and by using a bi-objective approach the decision maker is able to choose a trade-off between collecting profits and scattering teams. Two solution methods are proposed, a Multi-objective Genetic Algorithm and a Multi-objective Genetic Local Search Algorithm, both specialized in order to exploit the characteristics of the problem. It is demonstrated, by means of computational experiments on a new set of benchmark instances, that the proposed approach provides approximation sets with the desired characteristics. / Esta tese apresenta dois novos problemas de roteamento, ambos com funções objetivo voltadas para o posicionamento relativo das equipes durante o horizonte de roteamento. O posicionamento relativo resulta em uma dependência temporal e espacial entre rotas e é quantificado com uma métrica de dispersão não-linear, projetada para avaliar as distâncias instantâneas entre as equipes ao longo de um intervalo de tempo. Esta métrica permite a concepção de funções objetivo para aproximar as equipes durante a execução das rotas, quando minimizada, ou para dispersá-las, quando maximizada. Tanto a aproximação quanto a dispersão são características importantes de roteamento em algumas aplicações práticas, e dois novos problemas de otimização são propostos com esses objetivos opostos. O primeiro é uma variação do Problema de Múltiplos Caixeiros Viajantes, e seu objetivo é encontrar um conjunto de rotas em que os caixeiros viajam próximos uns dos outros, minimizando a dispersão. Um Algoritmo Genético com Busca Local é proposto para resolver o problema. Ele inclui operadores genéticos e vizinhanças especializados. Um novo conjunto de instâncias é proposto, adaptado para o novo problema de instâncias da literatura. Resultados computacionais mostram que a abordagem proposta proporciona soluções com as características desejadas de dispersão mínima. O segundo problema é um problema de roteamento de arcos biobjetivo em que as rotas devem ser construídas de modo a maximizar o lucro recolhido e o distanciamento entre as equipes. A maximização da métrica promove a dispersão das equipes durante a execução das rotas. Normalmente, os objetivos de lucro e dispersão são conflitantes, e com uma abordagem biobjetivo o tomador de decisão é capaz de avaliar a troca entre a coleta de lucros e a dispersão de equipes. Dois métodos de solução são propostos, um Algoritmo Genético Multiobjetivo e um Algoritmo Genético Multiobjetivo com Busca Local, ambos especializados para explorar as características do problema. É demonstrado, por meio de experimentos computacionais sobre um novo conjunto de instâncias, que a abordagem proposta fornece conjuntos de aproximação com as características desejadas.

This master thesis deals with various mathematical models, which can be used for designing the location of collection points for various fractions of municipal waste with consideration of walking distance, economic demands and utilization of allocated capacities. Scripts for generating input datasets for applied models from basic input data, which are address points with population and GPS coordinates, is also included in the thesis. The model was implemented in GAMS and the script was written in VBA in Microsoft Excel. Model was used in case study. Results of single and multi-criteria approaches are analyzed and compared.

Orientador: Antônio Fernando Branco Costa / Resumo: O presente trabalho desenvolveu um modelo matemático que contribui para o projeto de redes cicloviárias conexas e integradas ao sistema de transporte público por ônibus em áreas urbanas, fazendo uso da Otimização Multiobjetivo (OM) por meio da Programação Linear Inteira Mista (MILP ou MIP). A investigação dos critérios de infraestrutura que influenciam a demanda cicloviária e que deveriam compor a modelagem matemática foi realizada por meio da Revisão da Literatura e cinco critérios identificados, referentes ao: Conforto, Segurança, Objetividade, Intermodalidade e Continuidade. Cada critério é composto por uma série de subcritérios, dezesseis no total, classificados como parâmetros de projeto de entrada e/ou de saída para o modelo matemático, segundo funções objetivos e restrições. Uma aplicação do modelo foi realizada em um caso real para cidade de grande porte, em São José dos Campos – SP, e obtidas soluções exatas com redes parcialmente conexas (abordagem 1) e redes totalmente conexas (abordagem 2), integradas aos pontos de parada de ônibus e as linhas de ônibus da região delimitada, por meio da linguagem de modelagem General Algebric Modeling System (GAMS) e o solver CPLEX. Os resultados obtidos foram aderentes a realidade da macrozona de tráfego na região estudada e contribuem para o planejamento urbano como validado pela Secretaria de Mobilidade Urbana de São José dos Campos. A análise de diversos cenários para o modelo matemático, ponderando os objetivos do modelo, pos... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The present work created a mathematical model that contributes to design bikeway networks integrated to the public transport service by buses in urban areas, using the Network Multiobjective Optimization through Mixed by means of Mixed Integer Linear Programming (MILP or MIP). The investigation of the infrastructure criteria that influence cycling demand and that should set the mathematical modeling was carried out through the Literature Review and five criteria were identified, referring to: Comfort, Safety, Objectivity, Intermodality and Connectivity. Each criteria is composed of a subcriteria set, sixteen in total, which performed as input and/or output design parameters for the mathematical model, according to fitness functions and constraints. An application of the model was carried out in a real case in São Jose dos Campos city - Sao Paulo state, and exact solutions were obtained with partially connected networks (approach 1) and fully connected networks (approach 2), integrated to the stop points by bus and bus lines in the defined region, using the General Algebric Modeling System (GAMS) modeling language and the CPLEX solver. The results obtained were adherent to the reality of the traffic macrozone in the studied region and contribute to urban planning, as validated by the São José dos Campos Urban Mobility Secretariat. The analysis of several scenarios for the mathematical model, considering the model's objectives, made it possible to verify the behavior of the res... (Complete abstract click electronic access below) / Doutor

Wireless sensor networks is a broad subject with many applications and interesting research areas, such as optimization within connectivity and energy efficiency. One problem is that most published articles in this field use customized simulation environments and do not provide source code of their implementation. By not including aspects of implementation, it becomes difficult to determine how the results are achieved, which questions the validity and reliability of the works. This thesis aims to reproduce one of these researched methods, an algorithm that balances battery life with efficient routing within a network using fuzzy logic, with the goal to increase the reliability of the methodology within its field. The research question constructed on the foundation of these premises is thus “Is reproducibility satisfactory in a research work on a multi-objective routing algorithm, using fuzzy logic, in wireless sensor networks?, a case study by Minhas et al”. Two additional research questions emerge from the first one: “How does the reproduced algorithm perform in comparison to a selection of dif erent routing algorithms?” and “Is the reproduced algorithm, as is, applicable to a less idealistic environment?” To answer the research questions a computer simulation method is used to build, execute, and analyze the output of the algorithms. The results show that the implemented algorithm performs noticeably better in both lifetime and ratio to the shortest path compared with the original implementation, hinting towards the implementation and reproducibility deviating from expected results. The reproduced algorithm is also compared to two other algorithms under a different simulation environment, where it performs better in lifetime and packet delivery rate whilst performing slightly worse in energy efficiency and total energy consumption. Due to the significant differences in performance against the reproduced article’s implementation the study concludes that the reproducibility is not satisfactory. Lastly, it concludes that it does not perform well in a less idealistic simulation environment, making it less applicable.

No / Evolutionary membrane computing is an important research direction of membrane computing that aims to explore the complex interactions between membrane computing and evolutionary computation. These disciplines are receiving increasing attention. In this paper, an overview of the evolutionary membrane computing state-of-the-art and new results on two established topics in well defined scopes (membrane-inspired evolutionary algorithms and automated design of membrane computing models) are presented. We survey their theoretical developments and applications, sketch the differences between them, and compare the advantages and limitations. (C) 2014 Elsevier Inc. All rights reserved.

[ES] Las ciudades modernas están al límite de su capacidad en el plano horizontal. Muchas de ellas tienen un problema de tráfico muy complejo de paliar o resolver. La movilidad aérea urbana promete ser la revolución que puede resolver la saturación del tráfico en los futuros escenarios urbanos. Se espera que el crecimiento del mercado de la movilidad aérea urbana muestre una tendencia positiva constante, pero la tecnología asociada necesita aumentar su madurez. La gestión de múltiples vehículos aéreos, que dependen de tecnologías en auge como la inteligencia artificial y las estaciones de control en tierra automatizadas, requerirá una conexión tierra-aire-tierra sólida e ininterrumpida para completar sus trayectorias. La exigencia de una conexión ininterrumpida está naturalmente relacionada con una comprensión completa de los fenómenos que afectan al canal aire-tierra. La primera contribución es proponer un modelo de canal que pueda capturar las consecuencias de dichos fenómenos. Normalmente, un modelo de este tipo puede emitir el estado del canal en un punto determinado, prediciendo el estado del canal a lo largo de la trayectoria de la aeronave. Un modelo muy detallado exige herramientas y datos que proporcionen la información necesaria. La descripción y enumeración de cada pieza de información necesaria para una simulación de canal satisfactoria componen la segunda contribución. Una vez conocido el estado del canal, se pueden optimizar los puntos recorridos por la aeronave para cubrir aquellos con mejor rendimiento del canal. La tercera y última contribución es la propuesta de un conjunto de algoritmos de optimización para encontrar la ruta más adecuada. El algoritmo de optimización constituye el planificador de trayectorias, del que se espera que explore eficazmente el espacio de búsqueda y proponga una trayectoria que cumpla con los objetivos predefinidos: máxima calidad aire-tierra, disponibilidad y tiempo de vuelo. Cada método propuesto se pone a prueba en varios escenarios. Estos escenarios incluyen diversas situaciones que pueden estresar a los métodos y favorecer la elección de uno de ellos. Las situaciones incluidas son diferentes condiciones del terreno y zonas de exclusión aérea. / [CA] Les ciutats modernes estan al límit de la seua capacitat al pla horitzontal. Moltes tenen un problema de trànsit molt complex de pal·liar o resoldre. La mobilitat aèria urbana promet ser la revolució que pot resoldre la saturació del trànsit als futurs escenaris urbans. S'espera que el creixement del mercat de la mobilitat aèria urbana mostre una tendència positiva constant, però la tecnologia associada necessita augmentar-ne la maduresa. La gestió de múltiples vehicles aeris, que depenen de tecnologies en auge com la intel·ligència artificial i les estacions de control a terra automatitzades, requerirà una connexió terra-aire-terra sòlida i ininterrompuda per completar les seues trajectòries. L'exigència d'una connexió ininterrompuda està relacionada naturalment amb una comprensió completa dels fenòmens que afecten el canal aire-terra. La primera contribució és proposar un model de canal que puga capturar les conseqüències dels fenòmens esmentats. Normalment, un model d'aquest tipus pot emetre l'estat del canal en un punt determinat, predient l'estat del canal al llarg de la trajectòria de l'aeronau. Un model molt detallat exigeix eines i dades que proporcionen la informació necessària. La descripció i l'enumeració de cada peça d'informació necessària per a una simulació de canal satisfactòria componen la segona contribució. Una vegada conegut l'estat del canal, es poden optimitzar els punts recorreguts per l'aeronau per tal de cobrir aquells amb el millor rendiment del canal. La tercera i última contribució és la proposta d'un conjunt d'algorismes d'optimització per trobar la ruta més adequada. L'algorisme d'optimització constitueix el planificador de trajectòries, del qual s'espera que explore eficaçment l'espai de cerca i propose una trajectòria que complisca els objectius predefinits: màxima qualitat aire-terra, disponibilitat i temps de vol. Cada mètode proposat es posa a prova a diversos escenaris. Aquests escenaris inclouen diverses situacions que poden estressar els mètodes i afavorir-ne l'elecció. Les situacions incloses són diferents condicions del terreny i les zones d'exclusió aèria. / [EN] Modern cities are at the limit of their capacity in the horizontal plane. Many of them have a traffic problem that is highly complex to alleviate or solve. Urban air mobility promises to be the revolution that can solve traffic saturation in future urban scenarios. The growth of the urban air mobility market is expected to show a constant positive tendency, but the associated technology needs to raise its readiness levels. Managing aerial vehicle fleets, dependent on rising technologies such as artificial intelligence and automated ground control stations, will require a solid and uninterrupted connection to complete their trajectories. The requirement for an uninterrupted connection is naturally connected to a complete understanding of phenomena affecting the air-to-ground channel. The first contribution to the field is to propose a channel model that can capture the consequences of said phenomena. Typically, such a model can output the channel state at a given point, predicting the channel state throughout the aircraft's trajectory. A highly detailed model demands tools and data to deliver the necessary information. The description and enumeration of each piece of information required for a successful channel simulation compose the second contribution to the field. Once the channel state is known, the travelled points by the aircraft can be optimised to cover those with better channel performance. The third and last contribution to the field is proposing a set of optimisation algorithms to find the most suitable route. The optimisation algorithm forms the path planner, expected to efficiently explore the search space and propose a trajectory compliant with predefined objectives: maximum air-to-ground quality, availability, and flight time. Each proposed method is tested in various scenarios. These scenarios include various situations that can stress the methods and favour the choice of one. Included situations are different terrain conditions and no-fly zones. / Expósito García, A. (2023). Deterministic model of the radio channel applied to the optimization of the UAV trajectory for optimum air-to-ground communication in the environment of future urban scenarios [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/192614

During the assembly process of battery packs for electric vehicles, it is crucial to ensure that the cell-to-busbar joints can be produced with high quality, good reliability, and with minimal impact on the individual battery cells. This thesis project investigates the influence of different process parameters on the joint quality for laser welded dissimilar material cell-to-busbar joints. Nickel plated copper and steel plates, joined in an overlap configuration, are used as a simplified geometry, representing a cell-to-busbar joint. By the utilization of artificial neural network-based meta models, trained on numerical results from computational fluid dynamics simulations of the laser welding process, the joint quality is predicted and evaluated. The present thesis investigates how a set of optimized process parameters can be identified for the considered laser welded dissimilar material cell-to-busbar joints, in order to simultaneously maximize the interface width for the joints, and minimize the formation of undercuts and resulting in-process temperatures. NSGA-II is used to efficiently search for trade-off solutions, in an meta model-based multi-objective optimization approach, where the meta models are used to approximate the objectives, corresponding to the joint quality obtained from computational fluid dynamics simulations. With this, the time for one objective evaluation is reduced from approximately 9 hours, when the objectives are evaluated directly from computational fluid dynamics simulations, to only tenths of a second. With the proposed optimization approach, the Pareto-optimal front of trade-off solutions is identified, leading to the selection of three optimal solutions for validation. The validity of the proposed optimization approach, and the selected optimal solutions, are confirmed by means of both physical laser welding experiments and computational fluid dynamics simulations. It is shown that the selected optimal solutions, corresponding to three parameter setups, can be used to produce joints with large interface width and low in-process temperatures, without achieving a full penetration in the lower plate of the joint.

Multiobjective Stochastic Linear Programming is a relevant topic. As a matter of fact, many real life problems ranging from portfolio selection to water resource management may be cast into this framework. There are severe limitations in objectivity in this field due to the simultaneous presence of randomness and conflicting goals. In such a turbulent environment, the mainstay of rational choice does not hold and it is virtually impossible to provide a truly scientific foundation for an optimal decision. In this thesis, we resort to the bounded rationality and chance-constrained principles to define satisficing solutions for Multiobjective Stochastic Linear Programming problems. These solutions are then characterized for the cases of normal, exponential, chi-squared and gamma distributions. Ways for singling out such solutions are discussed and numerical examples provided for the sake of illustration. Extension to the case of fuzzy random coefficients is also carried out. / Decision Sciences

In this study, methodologies for modeling grey uncertainty in water resources systems are developed, specifically for the problems in two identified areas in water resources: waste load allocation in streams and floodplain planning. A water resources system is associated with some degree of uncertainty, due to randomness of hydrologic and hydraulic parameters, imprecision and subjectivity in management goals, inappropriateness in model selection, inexactness of different input parameters for inadequacy of data, etc. Uncertainty due to randomness of input parameters could be modeled by the probabilistic models, when probability distributions of the parameters may be estimated. Uncertainties due to imprecision in the management problem may be addressed by the fuzzy decision models. In addition, some parameters in any water resources problems need to be addressed as grey parameters, due to inadequate data for an accurate estimation but with known extreme bounds of the parameter values. Such inexactness or grey uncertainty in the model parameters can be addressed by the inexact or grey optimization models, representing the parameters as interval grey numbers. The research study presented in this thesis deals with the development of grey and fuzzy optimization models, and the combination of the two for water resources systems decision-making. Three grey fuzzy optimization models for waste load allocation, namely (i) Grey Fuzzy Waste Load Allocation Model (GFWLAM), (ii) two-phase GFWLAM and (iii) multiobjective GFWLAM, and a Grey Integer Programming (GIP) model for floodplain planning, are developed in this study. The Grey Fuzzy Waste Load Allocation Model (GFWLAM) for water quality management of river system addresses uncertainty in the membership functions for imprecisely stated management goals of the Pollution Control Agency (PCA) and dischargers. To address the imprecision in fixing the boundaries of membership functions (also known as membership parameters), the membership functions themselves are treated as imprecise in the model and the membership parameters are expressed as interval grey numbers. The conflict between the fuzzy goals of PCA and dischargers is modeled using the concept of fuzzy decision, but because of treating the membership parameters as interval grey numbers, in the present study, the notion of ‘fuzzy decision’ is extended to the notion of ‘grey fuzzy decision’. A terminology ‘grey fuzzy decision’ is used to represent the fuzzy decision resulting from the imprecise membership functions. The model provides flexibility for PCA and dischargers to specify their aspirations independently, as the membership parameters for membership functions are interval grey numbers in place of a deterministic real number. In the solution, optimal fractional removal levels of the pollutants are obtained in the form of interval grey numbers. This enhances the flexibility and applicability in decision-making, as the decision-maker gets a range of optimal solutions for fixing the final decision scheme considering technical and economic feasibility of the pollutant treatment levels. The methodology is demonstrated with the case studies of a hypothetical river system and the Tunga-Bhadra river system in Karnataka, India. Formulation of GFWLAM is based on the approach for solving fuzzy multiple objective optimization problem using max-min as the operator, which usually may not result in a unique solution. The two-phase GFWLAM captures all the alternative optimal solutions of the GFWLAM. The solution technique in the Phase 1 of two-phase GFWLAM is the same as that of GFWLAM. The Phase 2 maximizes upper bounds and minimizes lower bounds of decision variables, keeping the optimal value of goal fulfillment level same as obtained in the Phase 1. The two-phase GFWLAM gives the unique, widest, intervals of the optimal fractional removal levels of pollutant corresponding to the optimal value of goal fulfillment level. The solution increases the widths of interval-valued fractional removal levels of pollutants by capturing all the alternative optimal solutions and thus enhances the flexibility and applicability in decision-making. The model is applied to the case study of Tunga-Bhadra river system, which shows the existence of multiple solutions when the GFWLAM is applied to the same case study. The width of the interval of optimal fractional removal level plays an important role in the GFWLAM, as more width in the fractional removals implies a wider choice to the decision-makers and more applicability in decision-making. The multiobjective GFWLAM maximizes the width of the interval-valued fractional removal levels for providing a latitude in decision-making and minimizes the width of goal fulfillment level for reducing the system uncertainty. The multiobjective GFWLAM gives a new methodology to get a satisfactory deterministic equivalent of a grey fuzzy optimization problem, using the concept of acceptability index for a meaningful ranking between two partially or fully overlapping intervals. The resulting multiobjective optimization model is solved by fuzzy multiobjective optimization technique. The consistency of the solution is verified by solving the problem with fuzzy goal programming technique. The multiobjective GFWLAM avoids intermediate submodels unlike GFWLAM, so that the solution from a single deterministic equivalent of the GFWLAM adequately covers all possible situations. Although the solutions obtained from multiobjective GFWLAM provide more flexibility than those of the GFWLAM, its application is limited to grey fuzzy goals expressed by linear imprecise membership functions only, whereas GFWLAM has the capability to solve the model with any monotonic nonlinear imprecise membership functions also. The methodology is demonstrated with the case studies of a hypothetical river system and the Tunga-Bhadra river system in Karnataka, India. The Grey Integer Programming (GIP) model for floodplain planning is based on the floodplain planning model developed by Lund (2002), to identify an optimal mix of flood damage reduction options with probabilistic flood descriptions. The model demonstrates how the uncertainty of various input parameters in a floodplain planning problem can be modeled using interval grey numbers in the optimization model. The GIP model for floodplain planning does not replace a post-optimality analysis (e.g., sensitivity analysis, dual theory, parametric programming, etc.), but it provides additional information for interpretation of the optimal solutions. The results obtained from GIP model confirm that the GIP is a useful technique for interpretation of the solutions particularly when a number of potential feasible measures are available in a large scale floodplain planning problem. Though the present study does not directly compare the GIP technique with sensitivity analysis, the results indicate that the rigor and extent of post-optimality analyses may be reduced with the use of GIP for a large scale floodplain planning problem. Application of the GIP model is demonstrated with the hypothetical example as presented in Lund (2002).

Made available in DSpace on 2014-12-17T15:47:52Z (GMT). No. of bitstreams: 1 ThatianaCNS_DISSERT.pdf: 1637234 bytes, checksum: 8b38ce4a7a358efe654d9bb1c23c15bc (MD5) Previous issue date: 2010-03-02 / The distribution of petroleum products through pipeline networks is an important problem that arises in production planning of refineries. It consists in determining what will be done in each production stage given a time horizon, concerning the distribution of products from source nodes to demand nodes, passing through intermediate nodes. Constraints concerning storage limits, delivering time, sources availability, limits on sending or receiving, among others, have to be satisfied. This problem can be viewed as a biobjective problem that aims at minimizing the time needed to for transporting the set of packages through the network and the successive transmission of different products in the same pipe is called fragmentation. This work are developed three algorithms that are applied to this problem: the first algorithm is discrete and is based on Particle Swarm Optimization (PSO), with local search procedures and path-relinking proposed as velocity operators, the second and the third algorithms deal of two versions based on the Non-dominated Sorting Genetic Algorithm II (NSGA-II). The proposed algorithms are compared to other approaches for the same problem, in terms of the solution quality and computational time spent, so that the efficiency of the developed methods can be evaluated / A distribui??o de produtos de petr?leo atrav?s de redes de polidutos ? um importante problema que se coloca no planejamento de produ??o das refinarias. Consiste em determinar o que ser? feito em cada est?gio de produ??o dado um determinado horizonte de tempo, no que respeita ? distribui??o de produtos de n?s fonte ? procura de n?s, passando por n?s intermedi?rios. Restri??es relativas a limites de armazenamento, tempo de entrega, disponibilidade de fontes, limites de envio ou recebimento, entre outros, t?m de ser satisfeitas. Este problema pode ser visto como um problema biobjetivo, que visa minimizar o tempo necess?rio para transportar o conjunto de pacotes atrav?s da rede e o envio sucessivo de produtos diferentes no mesmo duto que ? chamado de fragmenta??o. Neste trabalho, s?o desenvolvidos tr?s algoritmos que s?o aplicados a esse problema: o primeiro algoritmo ? discreto e baseia-se na Otimiza??o por Nuvem de Part?culas (PSO), com procedimentos de busca local e path-relinking propostos como operadores de velocidade, o segundo e o terceiro algoritmos tratam de duas vers?es baseadas no Non-dominated Sorting Genetic Algorithm II (NSGA-II). Os algoritmos propostos s?o comparados a outras abordagens para o mesmo problema, em termos de qualidade de solu??o e tempo computacional despendido, a fim de se avaliar a efici?ncia dos m?todos desenvolvidos