878 resultados para swarm intelligence, optmization, recombination operators, theory, empirical study


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This thesis presents some different techniques designed to drive a swarm of robots in an a-priori unknown environment in order to move the group from a starting area to a final one avoiding obstacles. The presented techniques are based on two different theories used alone or in combination: Swarm Intelligence (SI) and Graph Theory. Both theories are based on the study of interactions between different entities (also called agents or units) in Multi- Agent Systems (MAS). The first one belongs to the Artificial Intelligence context and the second one to the Distributed Systems context. These theories, each one from its own point of view, exploit the emergent behaviour that comes from the interactive work of the entities, in order to achieve a common goal. The features of flexibility and adaptability of the swarm have been exploited with the aim to overcome and to minimize difficulties and problems that can affect one or more units of the group, having minimal impact to the whole group and to the common main target. Another aim of this work is to show the importance of the information shared between the units of the group, such as the communication topology, because it helps to maintain the environmental information, detected by each single agent, updated among the swarm. Swarm Intelligence has been applied to the presented technique, through the Particle Swarm Optimization algorithm (PSO), taking advantage of its features as a navigation system. The Graph Theory has been applied by exploiting Consensus and the application of the agreement protocol with the aim to maintain the units in a desired and controlled formation. This approach has been followed in order to conserve the power of PSO and to control part of its random behaviour with a distributed control algorithm like Consensus.

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Cloud computing is a practically relevant paradigm in computing today. Testing is one of the distinct areas where cloud computing can be applied. This study addressed the applicability of cloud computing for testing within organizational and strategic contexts. The study focused on issues related to the adoption, use and effects of cloudbased testing. The study applied empirical research methods. The data was collected through interviews with practitioners from 30 organizations and was analysed using the grounded theory method. The research process consisted of four phases. The first phase studied the definitions and perceptions related to cloud-based testing. The second phase observed cloud-based testing in real-life practice. The third phase analysed quality in the context of cloud application development. The fourth phase studied the applicability of cloud computing in the gaming industry. The results showed that cloud computing is relevant and applicable for testing and application development, as well as other areas, e.g., game development. The research identified the benefits, challenges, requirements and effects of cloud-based testing; and formulated a roadmap and strategy for adopting cloud-based testing. The study also explored quality issues in cloud application development. As a special case, the research included a study on applicability of cloud computing in game development. The results can be used by companies to enhance the processes for managing cloudbased testing, evaluating practical cloud-based testing work and assessing the appropriateness of cloud-based testing for specific testing needs.

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Competence development is considered a preventive strategy of burnout. At an organizational context some competences could be linked as precursors or consequences. In self-assessment of competence development, students perceive stress tolerance as a priority competence to ameliorate. Moreover employers and recruitment consultants agree that this is a new authentic challenge for organizations. The main reasons of this result are debated, this study should consider the importance of competence development from a holistic point of view. In addition it considers the exploration of the relationship between stress tolerance and competence development, according to Conservation Resources (COR) theory (Hobfoll 1988, 1989, 1998, 2004) where the resource loss is considered the principal component in the stress process

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This paper proposes a swarm intelligence long-term hedging tool to support electricity producers in competitive electricity markets. This tool investigates the long-term hedging opportunities available to electric power producers through the use of contracts with physical (spot and forward) and financial (options) settlement. To find the optimal portfolio the producer risk preference is stated by a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance estimation and the expected return are based on a forecasted scenario interval determined by a long-term price range forecast model, developed by the authors, whose explanation is outside the scope of this paper. The proposed tool makes use of Particle Swarm Optimization (PSO) and its performance has been evaluated by comparing it with a Genetic Algorithm (GA) based approach. To validate the risk management tool a case study, using real price historical data for mainland Spanish market, is presented to demonstrate the effectiveness of the proposed methodology.

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This paper addresses the optimal involvement in derivatives electricity markets of a power producer to hedge against the pool price volatility. To achieve this aim, a swarm intelligence meta-heuristic optimization technique for long-term risk management tool is proposed. This tool investigates the long-term opportunities for risk hedging available for electric power producers through the use of contracts with physical (spot and forward contracts) and financial (options contracts) settlement. The producer risk preference is formulated as a utility function (U) expressing the trade-off between the expectation and the variance of the return. Variance of return and the expectation are based on a forecasted scenario interval determined by a long-term price range forecasting model. This model also makes use of particle swarm optimization (PSO) to find the best parameters allow to achieve better forecasting results. On the other hand, the price estimation depends on load forecasting. This work also presents a regressive long-term load forecast model that make use of PSO to find the best parameters as well as in price estimation. The PSO technique performance has been evaluated by comparison with a Genetic Algorithm (GA) based approach. A case study is presented and the results are discussed taking into account the real price and load historical data from mainland Spanish electricity market demonstrating the effectiveness of the methodology handling this type of problems. Finally, conclusions are dully drawn.

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Genetic Algorithms (GAs) are adaptive heuristic search algorithm based on the evolutionary ideas of natural selection and genetic. The basic concept of GAs is designed to simulate processes in natural system necessary for evolution, specifically those that follow the principles first laid down by Charles Darwin of survival of the fittest. On the other hand, Particle swarm optimization (PSO) is a population based stochastic optimization technique inspired by social behavior of bird flocking or fish schooling. PSO shares many similarities with evolutionary computation techniques such as GAs. The system is initialized with a population of random solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. PSO is attractive because there are few parameters to adjust. This paper presents hybridization between a GA algorithm and a PSO algorithm (crossing the two algorithms). The resulting algorithm is applied to the synthesis of combinational logic circuits. With this combination is possible to take advantage of the best features of each particular algorithm.

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Investigação no âmbito do Projeto de Doutoramento(PhD), especialidade de Gestão Global, Estratégia e Desenvolvimento Empresarial (ISCTE-IUL - 2012, classificação de “Aprovado com Muito Bom”).

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The forces of globalization are changing the skills and competences required by effective global leadership. Accordingly, Business Schools (BSs) must adapt curriculums to the new queries so they, in fact, do develop future leader able to meet the challenges ahead. Increasing attention is being placed on global mindset (GM). Yet, this concept lacks research support. To help fulfilling this gap this research analyzes the effect that cultural intelligence (CQ) and a set of both personal and psychological characteristics have on GM enhancement. Based on a sample of academic students (N=220), findings suggested that CQ, vacations abroad and cosmopolitanism directly increase GM, while # language, PsyCap, TA and CSA do it indirectly. Practical implications for BSs and conclusions finalize this study.

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The aim of this research is to investigate if a celebrity can be a mediator between two brands so that a negative event happening to one brand can spill over to a completely unrelated brand, which shares with the first brand only the celebrity endorser. Even though celebrity endorsement is a popular marketing strategy and celebrities often endorse multiple brands, so far there has not been any systematic study on this topic. Drawing on Associative Network Theory and the Meaning Transfer Model as theoretical framework, this research finds out that negative publicity about a brand can spill over and thereby not only hurt consumers’ attitude toward the celebrity endorser but also toward a second brand that is endorsed by the same celebrity. An unexpected finding is that celebrities can act as a protective shield for brands by weakening the direct impact of negative publicity.

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Following major reforms of the British National Health Service (NHS) in 1990, the roles of purchasing and providing health services were separated, with the relationship between purchasers and providers governed by contracts. Using a mixed multinomial logit analysis, we show how this policy shift led to a selection of contracts that is consistent with the predictions of a simple model, based on contract theory, in which the characteristics of the health services being purchased and of the contracting parties influence the choice of contract form. The paper thus provides evidence in support of the practical relevance of theory in understanding health care market reform.

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Mergers and acquisitions (M&A) have played very important role in restructuring the pulp and paper industry (PPI). The poor performance and fragmented nature of the industry, overcapacity problems, and globalisation have driven companies to consolidate. The objective of this thesis was to examine how PPI acquirers’ have performed subsequent M&As and whether the deal characteristics have had any impact on performance. Based on the results it seems that PPI companies have not been able to enhance their performance in the long run after M&As although the per-formance of acquiring firms has remained above the industry median, and deal characteristics or the amount of premiums paid do not seem to have had any effect. The statistical significance of the results was tested with change model and regression analysis. Performance was assessed with accrual, cash flow, and market based indicators. Results are congruent with behavioural theory: managers and investors seem to be overoptimistic in determining the synergies from M&As.

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The study examines the internationalisation process of a contemporary SME firm and explores the impact of its business network on this development. The objective of the study is to understand SME internationalisation and its dynamics from a network perspective. The purpose of this research project is to describe and explore the development process of a firm and its business network by identifying the changes, critical events and influence factors that form this development. It is a qualitative case study, which focuses on a Finnish focal firm and its respective business network as it expands into the Greek market. It is a longitudinal research process, which covers a period of time from 1994 to 2004. The empirical study concentrates on the paper trading and converting business. The study builds on the network theory and the framework provided by Johanson and Mattsson's (1988) model on network internationalisation. The incremental internationalisation theories and network theories form the theoretical focus. The research project is organised according to a process view. The focal firm evolves from a domestically-oriented small subsidiary into an internationally experienced company, which has activities in several market areas and numerous business networks in various market segments and product categories. The findings illustrate the importance of both the domestic and foreign business network context in a firm's internationalisation process. The results of the study suggest theoretical modifications on a firm's internationalisation process by broadening the perspective and incorporating the strategic context of a firm. The findings suggest that internationalisation process is a non-linear process, which does not have a deterministic order in its development. The findings emphasise the significance of relational networks, both managerial and entrepreneurial, for establishing position in foreign markets. It implies that a firm's evolution is significantly influenced by its business network and by critical events. Business networks gain coherence due to common goals and they use accumulated capabilities to exploit market opportunities. The business network sets constraints and provides opportunities, which makes the related decision making strategically important. The firm co-evolves with its business network. The research project provides an instrumental case study with a description of an SME internationalisation process. It contributes to existing knowledge by illustrating dynamics in an international business network and by pinpointing the importance of suppliers, customers, partners, ownerships and competition to the internationalisation process.

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Corporate events as an effective part of marketing communications strategy seem to be underestimated in Finnish companies. In the rest of the Europe and the USA, investments in events are increasing, and their share of the marketing budget is significant. The growth of the industry may be explained by the numerous advantages and opportunities that events provide for attendees, such as face-to-face marketing, enhancing corporate image, building relationships, increasing sales, and gathering information. In order to maximize these benefits and return on investment, specific measurement strategies are required, yet there seems to exist a lack of understanding of how event performance should be perceived or evaluated. To address this research gap, this research attempts to describe the perceptions of and strategies for evaluating corporate event performance in the Finnish events industry. First, corporate events are discussed in terms of definitions and characteristics, typologies, and their role in marketing communications. Second, different theories on evaluating corporate event performance are presented and analyzed. Third, a conceptual model is presented based on the literature review, which serves as a basis for the empirical research conducted as an online questionnaire. The empirical findings are to a great extent in line with the existing literature, suggesting that there remains a lack of understanding corporate event performance evaluation, and challenges arise in determining appropriate measurement procedures for it. Setting clear objectives for events is a significant aspect of the evaluation process, since the outcomes of events are usually evaluated against the preset objectives. The respondent companies utilize many of the individual techniques that were recognized in theory, such as calculating the number of sales leads and delegates. However, some of the measurement tools may require further investments and resources, thus restricting their application especially in smaller companies. In addition, there seems to be a lack of knowledge of the most appropriate methods in different contexts, which take into account the characteristics of the organizing party as well as the size and nature of the event. The lack of inhouse expertise enhances the need for third-party service-providers in solving problems of corporate event measurement.

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Business intelligence (BI) is an information process that includes the activities and applications used to transform business data into valuable business information. Today’s enterprises are collecting detailed data which has increased the available business data drastically. In order to meet changing customer needs and gain competitive advantage businesses try to leverage this information. However, IT departments are struggling to meet the increased amount of reporting needs. Therefore, recent shift in the BI market has been towards empowering business users with self-service BI capabilities. The purpose of this study was to understand how self-service BI could help businesses to meet increased reporting demands. The research problem was approached with an empirical single case study. Qualitative data was gathered with a semi-structured, theme-based interview. The study found out that case company’s BI system was mostly used for group performance reporting. Ad-hoc and business user-driven information needs were mostly fulfilled with self-made tools and manual work. It was felt that necessary business information was not easily available. The concept of self-service BI was perceived to be helpful to meet such reporting needs. However, it was found out that the available data is often too complex for an average user to fully understand. The respondents felt that in order to self-service BI to work, the data has to be simplified and described in a way that it can be understood by the average business user. The results of the study suggest that BI programs struggle in meeting all the information needs of today’s businesses. The concept of self-service BI tries to resolve this problem by allowing users easy self-service access to necessary business information. However, business data is often complex and hard to understand. Self-serviced BI has to overcome this challenge before it can reach its potential benefits.