This paper presents an investigation of genetic programming fitness landscapes. We propose a new indicator of problem hardness for tree-based genetic programming, called negative ...
Leonardo Vanneschi, Manuel Clergue, Philippe Colla...
Theoretically and empirically it is clear that a genetic algorithm with crossover will outperform a genetic algorithm without crossover in some fitness landscapes, and vice versa i...
This paper introduces a new component based model that makes it relatively simple to prove that certain types of landscapes are elementary. We use the model to reconstruct proofs ...
Abstract. Particle Swarm Optimisers (PSOs) search using a set of interacting particles flying over the fitness landscape. These are typically controlled by forces that encourage ...
The importance of tuning a search algorithm for the specific features of the target search space has been known for quite some time. However, when dealing with multiobjective prob...