When implementing a genetic algorithm, I understand the basic idea is to have an initial population of a certain size. Then, we pick two individuals from a population, construct two new individuals (using mutation and crossover), repeat this process X number of times and the replace the old population with the new population, based on selecting the fittest.
In this method, the population size remains fixed. In reality in evolution, populations undergo fluctuations in population sizes (e.g. population bottlenecks, and new speciations).
I understand the disadvantages of variable populations sizes from a biological view are, for example, a bottleneck will reduce the population to minimal levels, so not much evolution will occur. Are there disadvantages to using variable population sizes in genetic algorithms, from a programming perspective? I was thinking the numbers per population could follow a distribution of some sort so they don't just randomly fluctuate erratically, but maybe this does not make sense to do.