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Hi,
I've been using both GWO, i.e. the gray wolf optimizer and MBH i.e. the monotonic basin hopping, with nlopt bobyqa internal optimizations and I was wondering which one is more efficient?
I've been using a population size of 100K to 400K max iterations=3 and number of generations =500.
I find that the GWO takes about 4X or so the time as compared to the MBH.
Is there any argument for using the GWO over the MBH? I'm thinking that it depends on the exact nature of my problem but in general, would the GWO be significantly better at finding solutions closer to the global optimum as compared to MBH?
Any thoughts?
Thanks
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Hi,
I've been using both GWO, i.e. the gray wolf optimizer and MBH i.e. the monotonic basin hopping, with nlopt bobyqa internal optimizations and I was wondering which one is more efficient?
I've been using a population size of 100K to 400K max iterations=3 and number of generations =500.
I find that the GWO takes about 4X or so the time as compared to the MBH.
Is there any argument for using the GWO over the MBH? I'm thinking that it depends on the exact nature of my problem but in general, would the GWO be significantly better at finding solutions closer to the global optimum as compared to MBH?
Any thoughts?
Thanks
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