The genesis for the idea began with the site CardShark [1], which allows private sellers to sell cards for collectible card games. At this site, if you buy 1 - 3 cards from a single seller, it costs you $1.30 in shipping. 4 - 7 cards costs you $1.60, and each additional fraction of 8 cards costs $0.45. The result of this is that you frequently can save money by consolidating your orders among just a few sellers, even if the per-item costs are higher.
As a simple example, let's say you want to buy Acquire [2] and Overrun [3]. The low price on Acquire is $0.25 and the low price on Overrun is $0.39, but these offers are from different sellers. Your total price to buy the cheapest items using a naive algorithm would thus be $0.25 + $1.30 + $0.39 + $1.30, or $3.24. But if you pay $0.50 *more* for the Overrun, you can get both cards from the same seller, still pay just $1.30 for shipping for that order, and save yourself a net $0.80. I'm looking for an algorithm that can efficiently explore this search space while finding the optimal set, without the possibility of being trapped in dead ends (e.g., sometimes the way to improve a three-seller order is to dump all the sellers in favor of two other sellers.) Unfortunately, I'm not familiar enough with search algorithms to know where to go from here. Any help? Thank you, - Joshua [1] http://www.cardshark.com [2] http://www.cardshark.com/magic/card_detail.asp?card_id=20912 [3] http://www.cardshark.com/magic/card_detail.asp?card_id=17408 --~--~---------~--~----~------------~-------~--~----~ You received this message because you are subscribed to the Google Groups "Algorithm Geeks" group. To post to this group, send email to [email protected] To unsubscribe from this group, send email to [EMAIL PROTECTED] For more options, visit this group at http://groups.google.com/group/algogeeks -~----------~----~----~----~------~----~------~--~---
