Meta-heuristic algorithms are problem-solving methods which try to find good-enough
solutions to very hard optimization problems, at a reasonable computation time, where …

This paper investigates the effects of process parameters on the joint strength and process
robustness when multi-layered joints of dissimilar metals are produced by ultrasonic metal …

Abstract A Building Information Modelling (BIM)-enabled computational approach was
presented in this paper for the automated specification of steel reinforcement to support the …

Industrial software often has many parameters that critically impact performance. Frequently,
these are left in a sub-optimal configuration for a given application because searching over …

Optimisation algorithms are commonly compared on benchmarks to get insight into
performance differences. However, it is not clear how closely benchmarks match the …

This research presents an approach that combines stacked Gaussian processes (stacked
GP) with target vector Bayesian optimization (BO) to solve multi-objective inverse problems …

This research focuses on optimizing multi-stage manufacturing processes using Bayesian
optimization (BO) with a robust Expected Improvement (EI) acquisition function. The aim is to …

The maintenance function in manufacturing has been gaining growing interest and
significance. Simulation based optimisation has a high potential in supporting maintenance …

Continuous flow reactors offer a host of advantages over their more traditional batch
counterparts. These include more controlled mixing, enhanced heat transfer and increased …

Evolutionary algorithms (EAs) constitute a branch of artificial intelligence utilised to evolve
solutions to solve optimisation problems abound in industry and research. EAs often …