The Neighbourhood Algorithm (NA) was introduced by Sambridge (1999a,b) as a direct search method for nonlinear inversion. This approach is applicable to a wide range of inversion problems, particularly those where the relationship between the observables (data) and the unknowns (a finite set of model parameters) is rather complex, e.g., fitting of seismic waveforms for Earth structure or source...

The Neighbourhood Algorithm (NA) was introduced by Sambridge (1999a,b) as a direct search method for nonlinear inversion. This approach is applicable to a wide range of inversion problems, particularly those where the relationship between the observables (data) and the unknowns (a finite set of model parameters) is rather complex, e.g., fitting of seismic waveforms for Earth structure or source...

In this paper we deal with the heuristic solution of the classical job shop problem. Both the constructive and the iterative phase of our algorithm apply insertion techniques combined with beam search. In the first phase we successively insert the operations into feasible partial schedules. In the iterative phase we generate paths in a particular neighbourhood graph instead of investigating the...

Given a connected, undirected graph whose edges are labelled (or coloured), the minimum labelling spanning tree (MLST) problem seeks a spanning tree whose edges have the smallest number of distinct labels (or colours). In recent work, the MLST problem has been shown to be NP-hard and some effective heuristics have been proposed and analysed. In this paper we present preliminary results of a cur...

Methods that leverage neighbourhood structures in high-dimensional image spaces have recently attracted attention. These approaches extract information from a new image using its "neighbours" in the image space equipped with an application-specific distance. Finding the neighbourhood of a given image is challenging due to large dataset sizes and costly distance evaluations. Furthermore, automat...

One of the most critical features for applying local search to timetabling problems is the definition of the neighbourhood structure. In fact, for most common timetabling problems, there is more than one neighbourhood structure that is sufficiently natural and intuitive to deserve investigation. The reason for considering combination of diverse neighbourhood is related to the diversification of...

This study proposes a novel binary version of the artificial bee colony algorithm based on genetic operators (GB-ABC) such as crossover and swap to solve binary optimization problems. Integrated to the neighbourhood searching mechanism of the basic ABC algorithm, the modification comprises four stages: (1) In neighbourhood of a (current) food source, randomly select two food sources from popula...