Most times I encounter this random metaphors for metaheuristic optimization they seem like a modified genetic algorithm to me. What do you think? Is there a way to remove the analogies/metaphors to better compare algorithms?
If you want to compare the ideas involved on the various metaheuristics, a good starting point for the comparison is to think of them as Population based vs Trajectory based. Population based metaheuristics works with the concept of create a solution that mix components of good solutions. Trajectory based metaheuristics works with the concept of creating a solution and iteratively do improving modifications(moves) on it. With the image below, you can visualize this dichotomy and other possibles parameters for comparison.
To compare performance, a common approach is to use time to target. Given a known solution and its objective value, how fast my metaheuristic achieve this value? This site provides a tool that helps in this task.