Abstract. We present and discuss the results of an experimental analysis in the design of Boolean networks by means of genetic algorithms. A population of networks is evolved with ...
Andrea Roli, Cristian Arcaroli, Marco Lazzarini, S...
This paper addresses the evolution of control strategies for a collective: a set of entities that collectively strives to maximize a global evaluation function that rates the perf...
Evolutionary and genetic algorithms (EAs and GAs) are quite successful randomized function optimizers. This success is mainly based on the interaction of different operators like ...
We present a simple framework for dealing with search spaces consisting of permutations. To demonstrate its usefulness, we build upon it a simple (1 + 1)-evolutionary algorithm fo...
The hypervolume indicator is widely used to guide the search and to evaluate the performance of evolutionary multi-objective optimization algorithms. It measures the volume of the ...