Microbiological inspired Swarm Intelligence for optimization in dynamic environments

In this paper we propose, implement and test a new approach to Dynamic Optimization inspired by microbiological swarms. Our approach makes use of the strengths of real bacteria, namely self organization, adaptation and natural selection to perform optimization. Finally, we test and show that our swarm significantly outperforms a state of the art approach by achieving comparable optimization in environments.