AbstractThis paper presents a real-coded memetic algorithm that combines a high diversity global exploration with an adaptive local search method to the most promising individuals ...
— A Cascaded model is introduced for mining large datasets using Genetic Programming without recourse to specialist hardware. Such an algorithm satisfies the seeming conflictin...
Peter Lichodzijewski, Malcolm I. Heywood, A. Nur Z...
This paper proposes a genetic algorithm (GA) with random immigrants for dynamic optimization problems where the worst individual and its neighbours are replaced every generation. I...
This paper reports an improvement to genetic programming (GP) search for the symbolic regression domain, based on an analysis of dissimilarity and mating. GP search is generally di...
Steven Gustafson, Edmund K. Burke, Natalio Krasnog...
Abstract- A new algorithm is presented for evolving Binary Decision Diagrams (BDD) that employs the neutrality implicit in the BDD representation. It is shown that an effortless ne...
AbstractInteractive evolutionary algorithms (IEA) often suffer from what is called the “user bottleneck.” In this paper, we propose and analyse a method to limit the user inter...
We study a selected group of hybrid EAs for solving CSPs, consisting of the best performing EAs from the literature. We investigate the contribution of the evolutionary component t...
In recent years the complexity of numerical computations in computational financial applications has been increased enormously. Monte Carlo algorithm is one of main tools in comput...
The most controversial part of genetic programming is its highly disruptive and potentially innovative subtree crossover operator. The clearest problem with the crossover operator...
Abstract- On marginal winter nights, highway authorities face a difficult decision as to whether or not to salt the road network. The consequences of making a wrong decision are s...