  Meta-solver approaches exploits a number of individual solvers to potentially
build a better solver. To assess the performance of meta-solvers, one can
simply adopt the metrics typically used for individual solvers (e.g., runtime
or solution quality), or employ more specific evaluation metrics (e.g., by
measuring how close the meta-solver gets to its virtual best performance). In
this paper, based on some recently published works, we provide an overview of
different performance metrics for evaluating (meta-)solvers, by underlying
their strengths and weaknesses.
