Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 7 of 7 for “"Continuous Optimisation"”.
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Novel Memetic Computing Structures for Continuous Optimisation
This thesis studies a class of optimisation algorithms, namely Memetic Computing Structures, and proposes a novel set of promising algorithms that move the first step towards an implementation for the automatic generation of optimisation algorithms for continuous domains. This thesis after a …
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Differential Evolution for Dynamic Constrained Continuous Optimisation
… this thesis, we choose the evolutionary dynamic optimisation methodology to tackle dynamic constrained problems. Dynamic constrained problems represent a common class of optimisation that occur in many real-world scenarios. Evolutionary algorithms are often considered very general search …
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Multicriteria optimisation in design for reliability
… for series-parallel systems’ reliability optimisation has been proposed developed and tested. It formulates the problem as a multi-criteria optimisation, to maximise the subsystem reliabilities while minimising the system cost modelled as a penalty function of component reliabilities, with …
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The Plant Propagation Algorithm for Discrete Optimisation
… heuristics for the so called NP-hard problems of optimisation. A particular algorithm which has been recently introduced and shown to be effective in continuous optimisation is the Plant Propagation Algorithm or PPA. Here, we intend to extend it to cope with combinatorial optimisation. In order to …
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Development of a framework for transitioning from a traditional campus to a smart campus using digital twin.
… initiation, analysis, full implementation, and continuous review, designed to support incremental and context-sensitive adoption. The framework was critically evaluated through expert and user-centric validation, confirming its practical relevance and improvement over existing approaches. …
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Advances in Optimisation of Model Parameters and Hyperparameters for Neural Networks
… to minimise some loss metric, so the chosen optimisation algorithm plays a fundamental role in the training process — both through the optimisation logic itself, and the auxiliary *hyperparameters* which configure the optimiser’s behaviour. Moreover, Machine Learning tasks often demand unique …
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Mathematical Optimisation Advances in Process Systems Engineering
… and to deal with these, special global optimisation methods are required. An important type of nonconvex problems is the bilinear programming problem. Bilinear problems are first and foremost interesting because of their many practical applications, including pooling problems. Over a …