There are many unsolved issues for swarm intelligence algorithms, such as the exploration versus exploitation, the population diversity, and the parameter setting.
Our theoretical result also contributes to the 'exploitation/exploration' conundrum in optimisation algorithm design, by suggesting that two commonly used approaches to enhancing exploration – increasing the population size, and increasing the disruptiveness of search operators – have quite distinct implications in terms of structural bias.
For exploration of the population structure within the Greenland Iceland system, we applied discriminant analysis of principal components (DAPC; Jombart et al. 2010) as implemented in R-package adegenet (Jombart 2008).
In the exploration of the population studied it was found that a significant difference between men and women was noted in most baseline characteristics other than in the age distribution and the hours of sleep (mean hours of sleep per night equalled 8; 95%CI 7.9 8.1).
This similarity is perhaps the result of the fact that the sequence space available for exploration by the populations is bounded by a unique starting point; they are all genotypically identical at the beginning of the evolution experiment.
Specifically, when the algorithm performs well in exploration, AMPS will shrink the population to enhance exploitation by periodically removing some inferior solutions that have low success rates.
However, the diversity of the population and exploration capability of the algorithm may deteriorate or may be completely lost through a very small number of generations, i.e., at the beginning of the optimization process, that cause problems such stagnation and/or premature convergence.
Once the exploration in each population was completed, then the MDs included in the built 9-variable models were retained with the purpose of creating new populations until 100 MDs.
However, due to data limitations acknowledged by the authors, the in-depth exploration of population sub-groups is not possible.
In contrast, AMPS will enlarge the population to improve exploration by introducing some reserved solutions.
