View article

Closed-loop optimization deals with problems in which candidate solutions are evaluated by conducting experiments, eg physical or biochemical experiments. Although this form of optimization is becoming more popular across the sciences, it may be subject to rather unexplored resourcing issues, as any experiment may require resources in order to be conducted. In this thesis we are concerned with understanding how evolutionary search is affected by three particular resourcing issues--ephemeral resource constraints (ERCs), changes of variables, and lethal environments--and the development of search strategies to combat these issues.