@article{nachbar:2000:meamhtaams,
title = {Molecular Evolution: Automated Manipulation of
Hierarchical Chemical Topology and Its Application to
Average Molecular Structures},
author = {Robert B. Nachbar},
journal = {Genetic Programming and Evolvable Machines},
month = {April},
number = {1/2},
pages = {57--94},
volume = {1},
year = {2000},
abstract = {A simple hierarchical data structure (tree) and
associated set of algorithms (written in Mathematica)
have been developed that permit the direct manipulation
of the topology of a molecule while simultaneously
maintaining valid chemical valence. Coupled with a
genetic algorithm optimization engine, these
computational tools can be used to optimize chemical
structures under the guidance of an appropriate fitness
function. A detailed study of the factors that
influence the performance of the method revealed that
it is strongly dependent on the size and complexity of
the evolved chemical structures. The effects of
population size and choice of genetic operators are
much smaller. The results of an exploration into the
discovery of average molecular structures using this
methodology is also described.},
issn = {1389-2576}, notes = {Article ID: 253705}, doi = {doi:10.1023/A:1010072431120},
keywords = {Mathematica,topological algorithms, average chemical descriptor, genetic hierarchy, programming, structure topology, }
}
::