From: Philipp Marcus <marcus_at_cip.ifi.lmu.de>

Date: Tue, 13 Apr 2010 13:15:13 +0200

Date: Tue, 13 Apr 2010 13:15:13 +0200

Hi, thanks for all your hints in your previous mail. My exact problem is: Given a set of items that have a certain dissimilarity amongst each other. Also given n knappsacks with unbounded capacity, the items should be allocated in such a way, that every item is packed to a knappsack and each knappsack has the lowest possible average dissimilarity among its items. (Put similar things in the same knappsack). Currently I also don't know exactly how to map it to the knappsack problem, to show that it is NP-complete (if it is, but I guess so). One aspect that would speak against seeing it as a knappsack problem is, that in my formulation the capacity of the knappsack and the volumes of items don't play any role. > Next remarks: > 1) You are using fd library. It is, according to my knowledge, > recommended to use ic library. Thats a good point. I decided to use fd because i have no ordering in my symbolic domain. Maybe I should check to transform it to ic_symbolic. I think this would make it much easier to integrate distances that are reals. <http://87.230.22.228/doc/bips/lib/fd/HNN-2.html> > 2) Domains of CLP variables should consist of integers (unless you are > using ic_symbolic library) > > [B1,B2,B3,B4,B5,B6] #:: ["B","C","D"] The definition of #:: in lib(fd) allows using lists AND variables. http://87.230.22.228/doc/bips/lib/fd/HNN-2.html Best regards, PhilippReceived on Tue Apr 13 2010 - 11:15:20 CEST

*
This archive was generated by hypermail 2.2.0
: Thu Feb 02 2012 - 02:31:58 CET
*