1.
Martins, Bruno VC; Brunetto, Gustavo; Sato, Fernando; Coluci, Vitor R; Galvao, Douglas S
Designing conducting polymers using bioinspired ant algorithms Journal Article
In: Chemical Physics Letters, vol. 453, no. 4, pp. 290–295, 2008.
@article{martins2008designing,
title = {Designing conducting polymers using bioinspired ant algorithms},
author = {Martins, Bruno VC and Brunetto, Gustavo and Sato, Fernando and Coluci, Vitor R and Galvao, Douglas S},
url = {http://www.sciencedirect.com/science/article/pii/S0009261408000845},
year = {2008},
date = {2008-01-01},
journal = {Chemical Physics Letters},
volume = {453},
number = {4},
pages = {290--295},
publisher = {Elsevier},
abstract = {Ant algorithms are inspired in real ants and the main idea is to create virtual ants that travel into the space of possible solutions depositing virtual pheromone proportional to how good a specific solution is. This creates an autocatalytic (positive feedback) process that can be used to generate automatic solutions to very difficult problems. In the present work we show that these algorithms can be used coupled to tight-binding Hamiltonians to design conducting polymers with pre-specified properties. The methodology is completely general and can be used for a large number of optimizations problems in materials science.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Ant algorithms are inspired in real ants and the main idea is to create virtual ants that travel into the space of possible solutions depositing virtual pheromone proportional to how good a specific solution is. This creates an autocatalytic (positive feedback) process that can be used to generate automatic solutions to very difficult problems. In the present work we show that these algorithms can be used coupled to tight-binding Hamiltonians to design conducting polymers with pre-specified properties. The methodology is completely general and can be used for a large number of optimizations problems in materials science.
2008
1.
Martins, Bruno VC; Brunetto, Gustavo; Sato, Fernando; Coluci, Vitor R; Galvao, Douglas S
Designing conducting polymers using bioinspired ant algorithms Journal Article
In: Chemical Physics Letters, vol. 453, no. 4, pp. 290–295, 2008.
Abstract | Links | BibTeX | Tags: ANTS algorithms, Artificial Intelligence, Conducting Polymer, Design of Materials
@article{martins2008designing,
title = {Designing conducting polymers using bioinspired ant algorithms},
author = {Martins, Bruno VC and Brunetto, Gustavo and Sato, Fernando and Coluci, Vitor R and Galvao, Douglas S},
url = {http://www.sciencedirect.com/science/article/pii/S0009261408000845},
year = {2008},
date = {2008-01-01},
journal = {Chemical Physics Letters},
volume = {453},
number = {4},
pages = {290--295},
publisher = {Elsevier},
abstract = {Ant algorithms are inspired in real ants and the main idea is to create virtual ants that travel into the space of possible solutions depositing virtual pheromone proportional to how good a specific solution is. This creates an autocatalytic (positive feedback) process that can be used to generate automatic solutions to very difficult problems. In the present work we show that these algorithms can be used coupled to tight-binding Hamiltonians to design conducting polymers with pre-specified properties. The methodology is completely general and can be used for a large number of optimizations problems in materials science.},
keywords = {ANTS algorithms, Artificial Intelligence, Conducting Polymer, Design of Materials},
pubstate = {published},
tppubtype = {article}
}
Ant algorithms are inspired in real ants and the main idea is to create virtual ants that travel into the space of possible solutions depositing virtual pheromone proportional to how good a specific solution is. This creates an autocatalytic (positive feedback) process that can be used to generate automatic solutions to very difficult problems. In the present work we show that these algorithms can be used coupled to tight-binding Hamiltonians to design conducting polymers with pre-specified properties. The methodology is completely general and can be used for a large number of optimizations problems in materials science.
http://scholar.google.com/citations?hl=en&user=95SvbM8AAAAJ
