This is an interesting idea. Right now this particular model is embedded in a pretty large scalability spreadsheet, but I could probably extract the key variables and formulas. What's less clear to me is how to model this over time under a GA approach.
There are definitely points in the spreadsheet where it stops being a good idea to buy more new machines and instead becomes a better idea to add more RAM to your existing machines. So the GA solution would somehow need to take into account the number and type of machines available at a given time T in order to optimize what should happen at time T+1.
Do you have any sample code or resources you could point to?
Case #2 is generally the approach we're taking, with the added wrinkle that the jobs themselves are parallelizable. That is, that one very long job J could actually be split into jobs J1..Jn. The questions I'm faced with is what N should be in order to be most cost effective.
The best I've come up with is a glorified spreadsheet that estimates total build time and lets me tweak #of machines and # of split-up jobs, and watch the bottom line change. Gross but I can't think of anything better.
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There are definitely points in the spreadsheet where it stops being a good idea to buy more new machines and instead becomes a better idea to add more RAM to your existing machines. So the GA solution would somehow need to take into account the number and type of machines available at a given time T in order to optimize what should happen at time T+1.
Do you have any sample code or resources you could point to?
The best I've come up with is a glorified spreadsheet that estimates total build time and lets me tweak #of machines and # of split-up jobs, and watch the bottom line change. Gross but I can't think of anything better.
Can you expound on this a bit? I've looked at BSCW a few times now and couldn't figure out how it handled versioning of documents... Thanks. Ramon