We present a Kernighan-Lin style local improvement heuristic for genetic algorithms. We analyze the run-time cost of the heuristic. We demonstrate through experiments that the heur...
This paper combines the idea of a hierarchical distributed genetic algorithm with different interagent partnering strategies. Cascading clusters of sub-populations are built from ...
The purpose of this study is to identify the Hierarchical Wavelet Neural Networks (HWNN) and select important input features for each sub-wavelet neural network automatically. Base...
— 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...
The Building Block Hypothesis suggests that Genetic Algorithms (GAs) are well-suited for hierarchical problems, where efficient solving requires proper problem decomposition and a...