The size and complexity of systems based on multiple processing units demand techniques for the automatic diagnosis of their state. System-level diagnosis consists in determining ...
In this paper, we incorporate a diversity mechanism to the differential evolution algorithm to solve constrained optimization problems without using a penalty function. The aim is...
In many real-world design problems, uncertainties are often present and practically impossible to avoid. Many existing works on Evolutionary Algorithm (EA) for handling uncertaint...
For computer-automated design systems to scale to complex designs they must be able to produce designs that exhibit the characteristics of modularity, regularity and hierarchy –...
We present discrete stochastic mathematical models for the growth curves of synchronous and asynchronous evolutionary algorithms with populations structured according to a random ...
Mario Giacobini, Marco Tomassini, Andrea Tettamanz...
This paper focuses on the computation time of evolutionary algorithms. First, some exact expressions of the mean first hitting times of general evolutionary algorithms in finite...
A meta-GA (GA within a GA) is used to investigate evolving the parameter settings of genetic operators for genetic and evolutionary algorithms (GEA) in the hope of creating a self...
Jeff Clune, Sherri Goings, Bill Punch, Eric Goodma...
This paper introduces an evolutionary algorithm which uses multiple chromosomes to evolve solutions to a symbolic regression problem. Inspiration for this algorithm is provided by...
Rachel Cavill, Stephen L. Smith, Andrew M. Tyrrell
The identification of mechanisms by which constraints on phenotypic variability are tuned in nature, and the implementation of these mechanisms in Evolutionary Algorithms (EAs) ca...
Computing consensus trees amounts to finding a single tree that summarizes a collection of trees. Three evolutionary algorithms are defined for this problem, featuring characteri...