Exactly! is large neighborhood search. And I get your idea is very clever. thanks.
Juan Carlos. On Wed, Jun 18, 2008 at 3:08 PM, Guido Tack <[EMAIL PROTECTED]> wrote: > Juan Carlos wrote: > > Now I see, I was confused about how the backtrack works. >> >> The idea is a Local Search Method, first find a basic solution, and then >> make little changes till the best solution is found, here are the steps: >> >> 1)choose the best value for each variable (this value is selected by a >> function based on external information), once all the variables had been >> assigned thats a basic solution. >> 2) Based on that solution , re-assign some variables in order to find a >> better solution in a fast way. The variables that are going to be >> re-inserted are chosen by a function based on external information and the >> value is chosen by the same function of step 1. >> 3) repeat 2 till no solution left. >> >> By external information I mean the information of the problem instance. >> >> Now I have some ideas about how to implement this local search but they >> are not clear yet. Any suggestions are welcome. >> > > That sounds a lot like large neighborhood search. I'd try using a plain > BAB search to find a solution, and then start a nested search, where you > create a new space, assign some of the variables, and run some limited BAB > (e.g. using a time limit). Once you find a better solution there, you reuse > that for the original, "master" BAB search. If you don't find a better > solution within the time limit, just go on in the master search. > To implement this, you'll probably have to implement your own search > engines or at least modifiy ours, but it should be possible. > > Cheers, > Guido > >
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