Hi,
I want to divide curve with distance between points so it will be like this:
1--2---3----4-----5------6-------7-----, ...
with values in range 1 to 50, must be simple but im stuck..
tnx
the Options. For example, if we look at the default settings in this order:
Population: Number of iterations / generation 50 - Galapagos tries 50 slider positions each generation. When it finishes 50, it looks at the results and takes from the best results based on your fitness.
Initial Boost: Factor for the first generation 2. You want to ensure Galapagos sees as much of the solution space as possible in order to not miss any potential solutions. The first generation is multiplied by this factor. If Population is 50, the first generation will be 50x2 = 100 slider positions.
Maintain and Inbreeding deal with what you keep between Generations.
Max Stagnant: Number of generations to try AFTER finding a better solution 50. If Galapagos finds a great solution in Generation 2 (Gen 0 = 100 tries, Gen 1 = 50 tries, Gen 2 = 50 tries) it will go another 50 Generations (50x50 tries) before it stops to ensure it did not miss anything.
Your solution space consists of 11 options, which is much less than any of the other parameters are suggesting. Galapagos flails wildly in your case because you told it to. You told it to try 50x50(+50 for initial boost) number of times to find the best value.
Hence why I do not think this is the best option. You said it, this is not an optimization problem. If it is not an optimization problem, why use a genetic algorithm solver which is predominantly used for optimizing parameters?
I wouldn't necessarily want to see the definition, I'm more curious about the data. For example, can you send the data for 10 structural members and some load cases? (again, I could be entirely oversimplifying it).
In any case, I changed Max. Stagnant to 5, Population to 11. So Galapagos will stop (5x11)+11 tries AFTER the best solution is found. It found the solution pretty quickly.…
Added by Luis Fraguada at 6:07am on September 7, 2016