#### Computational Science Technical Note CSTN-215

# Geometric Firefly Algorithms on Graphical Processing Units

## A. V. Husselmann and K. A. Hawick

### Archived: 2013

**Abstract**

Geometric unification of Evolutionary Algorithms (EAs) has resulted
in
an expanding set of algorithms which are search space invariant. This
is important
since search spaces are not always parametric. Of particular interest
are combinatorial
spaces such as those of programs that are searchable by parametric
optimisers,
providing they have been specially adapted in this way. This typically
involves redefining
concepts of distance, crossover and mutation operators. We present
an informally
modified Geometric Firefly Algorithm for searching expression tree
space,
and accelerate the computation using Graphical Processing Units. We
also evaluate
algorithm efficiency against a geometric version of the Genetic Programming
algorithm with tournament selection. We present some rendering techniques
for visualising
the program problem space and therefore to aid in characterising algorithm
behaviour.

**Keywords:** firefly; GPU; geometric algorithm; genetic algorithm

**Full Document Text:** Not yet available.

**Citation Information:** BiBTeX database for CSTN Notes.

**BiBTeX reference:**

@INCOLLECTION{CSTN-215,
author = {Husselmann, A. V. and Hawick, K. A.},
title = {Geometric Firefly Algorithms on Graphical Processing Units},
booktitle = {Cuckoo Search and Firefly Algorithm},
publisher = {Springer},
year = {2014},
pages = {245--269},
owner = {dpplayne),
timestamp = {2015.01.20}
}

[
CSTN Index |
CSTN BiBTeX
]