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Abstract- The complexity of the static scheduling problem on heterogeneous resources has motivated the development of low complexity heuristics such as list scheduling. However, th...
Many retailers run loyalty card schemes for their customers offering incentives in the form of money off coupons. The total value of the coupons depends on how much the customer ha...
Stephen Swift, Amy Shi, Jason Crampton, Allan Tuck...
When evolutionary algorithms are used for solving numerical constrained optimization problems, how to deal with the relationship between feasible and infeasible individuals can dir...
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...