Is there a minimum limit to a pool (population) size when using the genetic algorithm to solve an optimization problem? For example a population of size 2.
Asked By : Declan Murphy
Answered By : Philippe Olivier
I had a similar question and emailed Inman Harvey from the University of Sussex (author of Artificial Evolution: A Continuing SAGA and The Microbial Genetic Algorithm). Here is his answer (emphasis mine):
What is an optimum population size? Why?
If, like the natural world, a trillion microbes can evolve in the sea in parallel with no cost to you, then the bigger the better. In practice, on a serial machine, 10 times the pop-size costs you 10 times the time. Experience, with rather little theory, suggests that pop sizes of 30 to 100 minimum get you quite a lot of the advantages that GAs have over hill-climbing (ie pop of 2). So rule of thumb is to start here.
So basically, the bigger the population the better, but realistically you often have to make compromises to reach your goal in a reasonable amount of time. When building a genetic algorithm, you have to guess what the optimal values are for a lot of parameters. There is no good answer. Mostly there is a lot of trial and error.
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Question Source : http://cs.stackexchange.com/questions/34019
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