Basically, meta-heuristics fall into two categories: single-solution and multiple-solution (population-based). If you use single particle then it is single-solution-based.
Of course, population-based is better than single-solution-based because it takes advantage of swarming such as communication between members, moving based on global best solution...
I'm imitating the mobility of a bacteria to collect data. Just like you've said, moving based on global best solution. The data collector is represented by a bacteria. In that case, using the equations to find the new positions of the collector is considered as a single-based solution or population-based solution ? I'm confused !
What I am talking about is If you use multiple bacteria in initialization step then exploration and exploitation each bacteria based on global best or between each other. That's population-based algorithms.
If you use single bacteria in initialization step, then improved just that single bacteria time-to-time. That's single-based algorithms.