When you get into heavy scheduling, it's handy to look into genetic algorithms. While they almost certainly won't give you the optimal solution (since it is NP-complete), they can usually do a very good job within reasonable resource constraints.
-Adam On 10/17/06, Guyren Howe <[EMAIL PROTECTED]> wrote:
On Oct 17, 2006, at 12:51 PM, Youri wrote: > I need to develop an Agenda (very common sorry), but it will have > to answer to some simple questions for a human, such as : > > > What is the 1st possibility for my patient to get an appointement? > (find the 1st possible date) > > My patient can only come on Fridays, what is the 1st possible date > of appointment? > > ... > > It is mainly a quick and dirty way to "optimize" an agenda for a > Doctor. > > > The agenda will be based on a DB. > > > Any suggestion will be apreciated. Worth pointing out here that scheduling problems are classic exemplars of NP-complete problems. Which is a fancy, propeller-head way of saying that for surprisingly small-seeming problems, you're likely to give up any hope of wanting a "best possible" solution, and instead settle for "decent". Just finding a single appointment time won't be an issue, but once you start trying to align two or three doctors' schedules with two or three patients who all have various desiderata for their times, your search space gets prohibitive very quickly. And trying to search that space in an on-disk database compounds the problem significantly. Regards, Guyren G Howe Relevant Logic LLC guyren-at-relevantlogic.com ~ http://relevantlogic.com REALbasic, PHP, Python programming PostgreSQL, MySQL database design and consulting Technical writing and training _______________________________________________ Unsubscribe or switch delivery mode: <http://www.realsoftware.com/support/listmanager/> Search the archives of this list here: <http://support.realsoftware.com/listarchives/lists.html>
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