118 resultados para Multi-Criteria Optimisation

em Instituto Politécnico do Porto, Portugal


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This study proposes a new methodology to increase the power delivered to any load point in a radial distribution network, through the identification of new investments in order to improve the repair time. This research work is innovative and consists in proposing a full optimisation model based on mixed-integer non-linear programming considering the Pareto front technique. The goal is to achieve a reduction in repair times of the distribution networks components, while minimising the costs of that reduction as well as non-supplied energy costs. The optimisation model considers the distribution network technical constraints, the substation transformer taps, and it is able to choose the capacitor banks size. A case study based on a 33-bus distribution network is presented in order to illustrate in detail the application of the proposed methodology.

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Effective legislation and standards for the coordination procedures between consumers, producers and the system operator supports the advances in the technologies that lead to smart distribution systems. In short-term (ST) maintenance scheduling procedure, the energy producers in a distribution system access to the long-term (LT) outage plan that is released by the distribution system operator (DSO). The impact of this additional information on the decision-making procedure of producers in ST maintenance scheduling is studied in this paper. The final ST maintenance plan requires the approval of the DSO that has the responsibility to secure the network reliability and quality, and other players have to follow the finalized schedule. Maintenance scheduling in the producers’ layer and the coordination procedure between them and the DSO is modelled in this paper. The proposed method is applied to a 33-bus distribution system.

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Solvent extraction is considered as a multi-criteria optimization problem, since several chemical species with similar extraction kinetic properties are frequently present in the aqueous phase and the selective extraction is not practicable. This optimization, applied to mixer–settler units, considers the best parameters and operating conditions, as well as the best structure or process flow-sheet. Global process optimization is performed for a specific flow-sheet and a comparison of Pareto curves for different flow-sheets is made. The positive weight sum approach linked to the sequential quadratic programming method is used to obtain the Pareto set. In all investigated structures, recovery increases with hold-up, residence time and agitation speed, while the purity has an opposite behaviour. For the same treatment capacity, counter-current arrangements are shown to promote recovery without significant impairment in purity. Recycling the aqueous phase is shown to be irrelevant, but organic recycling with as many stages as economically feasible clearly improves the design criteria and reduces the most efficient organic flow-rate.

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In the last twenty years genetic algorithms (GAs) were applied in a plethora of fields such as: control, system identification, robotics, planning and scheduling, image processing, and pattern and speech recognition (Bäck et al., 1997). In robotics the problems of trajectory planning, collision avoidance and manipulator structure design considering a single criteria has been solved using several techniques (Alander, 2003). Most engineering applications require the optimization of several criteria simultaneously. Often the problems are complex, include discrete and continuous variables and there is no prior knowledge about the search space. These kind of problems are very more complex, since they consider multiple design criteria simultaneously within the optimization procedure. This is known as a multi-criteria (or multiobjective) optimization, that has been addressed successfully through GAs (Deb, 2001). The overall aim of multi-criteria evolutionary algorithms is to achieve a set of non-dominated optimal solutions known as Pareto front. At the end of the optimization procedure, instead of a single optimal (or near optimal) solution, the decision maker can select a solution from the Pareto front. Some of the key issues in multi-criteria GAs are: i) the number of objectives, ii) to obtain a Pareto front as wide as possible and iii) to achieve a Pareto front uniformly spread. Indeed, multi-objective techniques using GAs have been increasing in relevance as a research area. In 1989, Goldberg suggested the use of a GA to solve multi-objective problems and since then other researchers have been developing new methods, such as the multi-objective genetic algorithm (MOGA) (Fonseca & Fleming, 1995), the non-dominated sorted genetic algorithm (NSGA) (Deb, 2001), and the niched Pareto genetic algorithm (NPGA) (Horn et al., 1994), among several other variants (Coello, 1998). In this work the trajectory planning problem considers: i) robots with 2 and 3 degrees of freedom (dof ), ii) the inclusion of obstacles in the workspace and iii) up to five criteria that are used to qualify the evolving trajectory, namely the: joint traveling distance, joint velocity, end effector / Cartesian distance, end effector / Cartesian velocity and energy involved. These criteria are used to minimize the joint and end effector traveled distance, trajectory ripple and energy required by the manipulator to reach at destination point. Bearing this ideas in mind, the paper addresses the planning of robot trajectories, meaning the development of an algorithm to find a continuous motion that takes the manipulator from a given starting configuration up to a desired end position without colliding with any obstacle in the workspace. The chapter is organized as follows. Section 2 describes the trajectory planning and several approaches proposed in the literature. Section 3 formulates the problem, namely the representation adopted to solve the trajectory planning and the objectives considered in the optimization. Section 4 studies the algorithm convergence. Section 5 studies a 2R manipulator (i.e., a robot with two rotational joints/links) when the optimization trajectory considers two and five objectives. Sections 6 and 7 show the results for the 3R redundant manipulator with five goals and for other complementary experiments are described, respectively. Finally, section 8 draws the main conclusions.

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The integration of wind power in eletricity generation brings new challenges to unit commitment due to the random nature of wind speed. For this particular optimisation problem, wind uncertainty has been handled in practice by means of conservative stochastic scenario-based optimisation models, or through additional operating reserve settings. However, generation companies may have different attitudes towards operating costs, load curtailment, or waste of wind energy, when considering the risk caused by wind power variability. Therefore, alternative and possibly more adequate approaches should be explored. This work is divided in two main parts. Firstly we survey the main formulations presented in the literature for the integration of wind power in the unit commitment problem (UCP) and present an alternative model for the wind-thermal unit commitment. We make use of the utility theory concepts to develop a multi-criteria stochastic model. The objectives considered are the minimisation of costs, load curtailment and waste of wind energy. Those are represented by individual utility functions and aggregated in a single additive utility function. This last function is adequately linearised leading to a mixed-integer linear program (MILP) model that can be tackled by general-purpose solvers in order to find the most preferred solution. In the second part we discuss the integration of pumped-storage hydro (PSH) units in the UCP with large wind penetration. Those units can provide extra flexibility by using wind energy to pump and store water in the form of potential energy that can be generated after during peak load periods. PSH units are added to the first model, yielding a MILP model with wind-hydro-thermal coordination. Results showed that the proposed methodology is able to reflect the risk profiles of decision makers for both models. By including PSH units, the results are significantly improved.

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This paper aims to present a multi-agent model for a simulation, whose goal is to help one specific participant of multi-criteria group decision making process.This model has five main intervenient types: the human participant, who is using the simulation and argumentation support system; the participant agents, one associated to the human participant and the others simulating the others human members of the decision meeting group; the directory agent; the proposal agents, representing the different alternatives for a decision (the alternatives are evaluated based on criteria); and the voting agent responsiblefor all voting machanisms.At this stage it is proposed a two phse algorithm. In the first phase each participantagent makes his own evaluation of the proposals under discussion, and the voting agent proposes a simulation of a voting process.In the second phase, after the dissemination of the voting results,each one ofthe partcipan agents will argue to convince the others to choose one of the possible alternatives. The arguments used to convince a specific participant are dependent on agent knowledge about that participant. This two-phase algorithm is applied iteratively.

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Performance evaluation increasingly assumes a more important role in any organizational environment. In the transport area, the drivers are the company’s image and for this reason it is important to develop and increase their performance and commitment to the company goals. This evaluation can be used to motivate driver to improve their performance and to discover training needs. This work aims to create a performance appraisal evaluation model of the drivers based on the multi-criteria decision aid methodology. The MMASSI (Multicriteria Methodology to Support Selection of Information Systems) methodology was adapted by using a template supporting the evaluation according to the freight transportation company in study. The evaluation process involved all drivers (collaborators being evaluated), their supervisors and the company management. The final output is a ranking of the drivers, based on their performance, for each one of the scenarios used.

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Multi-criteria decision analysis(MCDA) has been one of the fastest-growing areas of operations research during the last decades. The academic attention devoted to MCDA motivated the development of a great variety of approaches and methods within the field. These methods distinguish themselves in terms of procedures, theoretical assumptions and type of decision addressed. This diversity poses challenges to the process of selecting the most suited method for a specific real-world decision problem. In this paper we present a case study in a real-world decision problem arising in the painting sector of an automobile plant. We tackle the problem by resorting to the well-known AHP method and to the MCDA method proposed by Pereira and Fontes (2012) (MMASSI). By relying on two, rather than one, MCDA methods we expect to improve the confidence and robustness of the obtained results. The contributions of this paper are twofold: first, we intend to investigate the contrasts and similarities of the results obtained by distinct MCDA approaches (AHP and MMASSI); secondly, we expect to enrich the literature of the field with a real-world MCDA case study on a complex decision making problem since there is a paucity of applied research work addressing real decision problems faced by organizations.

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Multi-criteria decision analysis (MCDA) has been one of the fastest-growing areas of operations research during the last decades. The academic attention devoted to MCDA motivated the development of a great variety of approaches and methods within the field. These methods distinguish themselves in terms of procedures, theoretical assumptions and type of decision addressed. This diversity poses challenges to the process of selecting the most suited method for a specific real-world decision problem. In this paper we present a case study in a real-world decision problem arising in the painting sector of an automobile plant. We tackle the problem by resorting to the well-known AHP method and to the MCDA method proposed by Pereira and Fontes (2012) (MMASSI). By relying on two, rather than one, MCDA methods we expect to improve the confidence and robustness of the obtained results. The contributions of this paper are twofold: first, we intend to investigate the contrasts and similarities of the results obtained by distinct MCDA approaches (AHP and MMASSI); secondly, we expect to enrich the literature of the field with a real-world MCDA case study on a complex decision making problem since there is a paucity of applied research work addressing real decision problems faced by organizations.

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The main objective of this work is to report on the development of a multi-criteria methodology to support the assessment and selection of an Information System (IS) framework in a business context. The objective is to select a technological partner that provides the engine to be the basis for the development of a customized application for shrinkage reduction on the supply chains management. Furthermore, the proposed methodology di ers from most of the ones previously proposed in the sense that 1) it provides the decision makers with a set of pre-defined criteria along with their description and suggestions on how to measure them and 2)it uses a continuous scale with two reference levels and thus no normalization of the valuations is required. The methodology here proposed is has been designed to be easy to understand and use, without a specific support of a decision making analyst.

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Performance appraisal increasingly assumes a more important role in any organizational environment. In the trucking industry, drivers are the company's image and for this reason it is important to develop and increase their performance and commitment to the company's goals. This paper aims to create a performance appraisal model for trucking drivers, based on a multi-criteria decision aid methodology. The PROMETHEE and MMASSI methodologies were adapted using the criteria used for performance appraisal by the trucking company studied. The appraisal involved all the truck drivers, their supervisors and the company's Managing Director. The final output is a ranking of the drivers, based on their performance, for each one of the scenarios used. The results are to be used as a decision-making tool to allocate drivers to the domestic haul service.

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No ambiente altamente competitivo de hoje, um processo eficaz de seleção de fornecedores é muito importante para o sucesso de qualquer organização [33]. Esta dissertação procura determinar quais os critérios e métodos mais utilizados no problema da seleção de fornecedores, contribuindo assim para o apoio a entidades que pretendam iniciar uma seleção de fornecedores de uma forma mais eficaz. Para atingir os objetivos propostos, foi realizada uma análise de artigos que fazem a revisão literária dos métodos e critérios desde o ano de 1985 até ao ano 2012. Com os dados obtidos destas revisões, foi possível identificar quais os três principais métodos utilizados ao longo dos anos, sendo eles o DEA, AHP e Fuzzy set theory e os principais critérios utilizados na seleção de fornecedores. Nesta dissertação, é apresentada uma visão geral da tomada de decisão e os métodos utilizados na tomada de decisão multicritério. É abordado o problema da seleção de fornecedores, o seu processo de seleção e as revisões literárias dos métodos e critérios de seleção utilizados nos últimos anos. Por fim, é apresentada a contribuição para a seleção de fornecedores do estudo realizado durante o desenvolvimento desta dissertação, sendo apresentados e explicados os principais métodos de seleção de fornecedores, bem como os critérios utilizados.

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The research presented in this paper proposes a novel quantitative model for decomposing and assessing the Value for the Customer. The proposed approach builds on the different dimensions of the Value Network analysis proposed by Verna Allee having as background the concept of Value for the Customer proposed by Woodall. In this context, the Value for the Customer is modelled as a relationship established between the exchanged deliverables and a combination of tangible and intangible assets projected into their endogenous or exogenous dimensions. The Value Network Analysis of the deliverables exchange enables an in-depth understanding of this frontier and the implicit modelling of co-creation scenarios. The proposed Conceptual Model for Decomposing Value for the Customer combines several concepts: from the marketing area we have the concept of Value for the Customer; from the area of intellectual capital the concept of Value Network Analysis; from the collaborative networks area we have the perspective of the enterprise life cycle and the endogenous and exogenous perspectives; at last, the proposed model is supported by a mathematical formal description that stems from the area of Multi-Criteria Decision Making. The whole concept is illustrated in the context of a case study of an enterprise in the footwear industry (Pontechem). The merits of this approach seem evident from the contact with Pontechem as it provides a structured approach for the enterprises to assess the adequacy of their value proposition to the client/customer needs and how these relate to their endogenous and/or exogenous tangible or intangible assets. The proposed model, as a tool, may therefore be a useful instrument in supporting the commercialisation of new products and/or services.

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Os Sistemas de Apoio à Tomada de Decisão em Grupo (SADG) surgiram com o objetivo de apoiar um conjunto de decisores no processo de tomada de decisão. Uma das abordagens mais comuns na literatura para a implementação dos SADG é a utilização de Sistemas Multi-Agente (SMA). Os SMA permitem refletir com maior transparência o contexto real, tanto na representação que cada agente faz do decisor que representa como no formato de comunicação utilizado. Com o crescimento das organizações, atualmente vive-se uma viragem no conceito de tomada de decisão. Cada vez mais, devido a questões como: o estilo de vida, os mercados globais e o tipo de tecnologias disponíveis, faz sentido falar de decisão ubíqua. Isto significa que o decisor deverá poder utilizar o sistema a partir de qualquer local, a qualquer altura e através dos mais variados tipos de dispositivos eletrónicos tais como tablets, smartphones, etc. Neste trabalho é proposto um novo modelo de argumentação, adaptado ao contexto da tomada de decisão ubíqua para ser utilizado por um SMA na resolução de problemas multi-critério. É assumido que cada agente poderá utilizar um estilo de comportamento que afeta o modo como esse agente interage com outros agentes em situações de conflito. Sendo assim, pretende-se estudar o impacto da utilização de estilos de comportamento ao longo do processo da tomada de decisão e perceber se os agentes modelados com estilos de comportamento conseguem atingir o consenso mais facilmente quando comparados com agentes que não apresentam nenhum estilo de comportamento. Pretende-se ainda estudar se o número de argumentos trocados entre os agentes é proporcional ao nível de consenso final após o processo de tomada de decisão. De forma a poder estudar as hipóteses de investigação desenvolveu-se um protótipo de um SADG, utilizando um SMA. Desenvolveu-se ainda uma framework de argumentação que foi adaptada ao protótipo desenvolvido. Os resultados obtidos permitiram validar as hipóteses definidas neste trabalho tendo-se concluído que os agentes modelados com estilos de comportamento conseguem na maioria das vezes atingir um consenso mais facilmente comparado com agentes que não apresentam nenhum estilo de comportamento e que o número de argumentos trocados entre os agentes durante o processo de tomada de decisão não é proporcional ao nível de consenso final.

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This paper describes the development and the implementation of a multi-agent system for integrated diagnosis of power transformers. The system is divided in layers which contain a number of agents performing different functions. The social ability and cooperation between the agents lead to the final diagnosis and to other relevant conclusions through integrating various monitoring technologies, diagnostic methods and data sources, such as the dissolved gas analysis.