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Collective combinatorial optimisation as judgment aggregation
In many settings, a collective decision has to be made over a set of alternatives that has a combinatorial structure: important examples are...
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Solving many-objective optimisation problems using partial dominance
Most optimisation problems have multiple, often conflicting, objectives. Due to the conflicting objectives, a single solution does not exist, and...
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Data-Flow Analysis and Optimisation
Most compilers perform some optimisations on the code that is generated by the main phases of the compiler. These optimisations often follow a common...
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SELF-EdiT: Structure-constrained molecular optimisation using SELFIES editing transformer
Structure-constrained molecular optimisation aims to improve the target pharmacological properties of input molecules through small perturbations of...
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Optimisation
Optimisation is one of the most fundamental areas of numerical computing. From simple root finding to advanced machine learning, optimisation is...
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Deep spatial and tonal data optimisation for homogeneous diffusion inpainting
Diffusion-based inpainting can reconstruct missing image areas with high quality from sparse data, provided that their location and their values are...
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An electromagnetic shape optimisation for perfectly electric conductors by the time-domain boundary integral equations
This study proposes a shape optimisation framework for unsteady electromagnetic scattering problems on the basis of the time-domain boundary integral...
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Multi-guide particle swarm optimisation archive management strategies for dynamic optimisation problems
This study presents archive management approaches for dynamic multi-objective optimisation problems (DMOPs) using the multi-guide particle swarm...
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SonOpt: understanding the behaviour of bi-objective population-based optimisation algorithms through sound
We present an extension of SonOpt, the first ever openly available tool for the sonification of bi-objective population-based optimisation...
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Optimisation of electrical Impedance tomography image reconstruction error using heuristic algorithms
Preventing living tissues’ direct exposure to ionising radiation has resulted in tremendous growth in medical imaging and e-health, enhancing...
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Global–local multidisciplinary optimisation for the evaluation of local constraints on finer meshes in preliminary aircraft design
Multidisciplinary design optimisation (MDO) is a methodology increasingly being used in the preliminary design of aircraft. To limit the...
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Model-based cloud service deployment optimisation method for minimisation of application service operational cost
Many currently existing cloud cost optimisation solutions are aimed at cloud infrastructure providers, and they often deal only with specific types...
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Fall compensation detection from EEG using neuroevolution and genetic hyperparameter optimisation
AbstractDetecting fall compensatory behaviour from large EEG datasets poses a difficult problem in big data which can be alleviated by evolutionary...
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Towards a software tool for general meal optimisation
The following work presents a software solution capable of designing general meal plans which approach an optimal match of nutritional...
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Contextual Robust Optimisation with Uncertainty Quantification
We propose two pipelines for convex optimisation problems with uncertain parameters that aim to improve decision robustness by addressing the...
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Integrating Bayesian and Evolutionary Approaches for Multi-objective Optimisation
Both Multi-Objective Evolutionary Algorithms (MOEAs) and Multi-Objective Bayesian Optimisation (MOBO) are designed to address challenges posed by...
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Surrogate-assisted hyper-parameter search for portfolio optimisation: multi-period considerations
Portfolio management is a multi-period multi-objective optimisation problem subject to various constraints. However, portfolio management is treated...
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Optimistic optimisation of composite objective with exponentiated update
This paper proposes a new family of algorithms for the online optimisation of composite objectives. The algorithms can be interpreted as the...
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Hybrid cuckoo finch optimisation based machine learning classifier for seizure prediction using EEG signals in IoT network
The Internet of Things (IoT) is an indispensable part of the healthcare system since it creates a link between the doctor and the patient for remote...
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Optimal Allocation of PV-Based Distributed Generations and Scheduling of Battery Storage in Grid-Connected Micro-grid Using Bi-level Optimisation
The presence of photovoltaic-based distributed generation in distribution networks brings a concern regarding intermittency of power generation. This...
