Real-world applications generally distinguish themselves from theoretical developments in that they are much more complex and varied. As a consequence, better models require more d...
In case the objective function to be minimized is not known analytically and no assumption can be made about the single extremum, global optimization (GO) methods must be used. Pap...
Abstract— This paper presents a Markov model for the convergence of multi-parent genetic algorithms (MPGAs). The proposed model formulates the variation of gene frequency caused ...
An L-system or Lindenmayer system consists of a grammar and an interpreter. The grammar contains an axiom, usually a short string, that the grammar expands into a long, complex st...
Daniel A. Ashlock, Stephen P. Gent, Kenneth Mark B...
We present a homomorphous mapping that converts problems with linear equality constraints into fully unconstrained and lower-dimensional problems for optimization with PSO. This ap...
—In this paper, the performance of dynamic multi-swarm particle swarm optimizer (DMS-PSO) on the set of benchmark functions provided for the CEC2008 Special Session on Large Scal...
The XCS Learning Classifier System has traditionally used roulette wheel selection within its genetic algorithm component. Recently, tournament selection has been suggested as prov...
A grouping genetic algorithm (GGA) for the university course timetabling problem is outlined. We propose six different fitness functions, all sharing the same common goal, and look...
We consider the (1+λ) evolution strategy, an evolutionary algorithm for minimization in Rn , using isotropic mutations. Thus, for instance, Gaussian mutations adapted by the 1/5-r...
An investigation is conducted into the effects of a complex mapping between genotype and phenotype upon a simulated evolutionary process. A model of embryogeny is utilised to grow ...