  Bacteria have been a source of inspiration for the design of evolutionary
algorithms. At the beginning of the 20th century synthetic biology was born, a
discipline whose goal is the design of biological systems that do not exist in
nature, for example, programmable synthetic bacteria. In this paper, we
introduce as a novelty the designing of evolutionary algorithms where all the
steps are conducted by synthetic bacteria. To this end, we designed a genetic
algorithm, which we have named BAGA, illustrating its utility solving simple
instances of optimization problems such as function optimization, 0/1 knapsack
problem, Hamiltonian path problem. The results obtained open the possibility of
conceiving evolutionary algorithms inspired by principles, mechanisms and
genetic circuits from synthetic biology. In summary, we can conclude that
synthetic biology is a source of inspiration either for the design of
evolutionary algorithms or for some of their steps, as shown by the results
obtained in our simulation experiments.

Neural and Evolutionary Computing;Multiagent Systems