W dniu 2010-04-13 11:07, Philipp Marcus pisze: > Do you see a possibility to take these not-passed distances in the VRP > into account? > Not easily. I missed the information you should measure also distances vehicles don't pass. I do not think that with this constraint VRP is a good idea. But I would start from the beginning. What exactly problem you have? :) > What I've tried so far is the following that can be called by: > assignItems([B1,B2,B3,B4,B5,B6],Measure) > > What is wrong with this solution? It seems to be ok (see below for small remarks). > Measure #= Measure1 + Measure2 + Measure3/3, > Here you miss brackets... > branch_and_bound:minimize(labeling([B1,B2,B3,B4,B5,B6]),Measure). > > sigma(Items,Knappsack,Value) :- > I understand this predicate calculates sum of dissimilarities of items belonging to knappsack Knappsack. > (Id1 #\= Id2 -> > Id1 and Id2 are not CLP variables so you should use \== operator instead of #\=. > dist(Id1,Id2,Dist) infers most, "infers most" does not change anything here. Id1 and Id2 are atoms so Dist is uniquely determined. Best regards -- [ Wit Jakuczun http://pl.linkedin.com/in/jakuczunwit ]Received on Tue Apr 13 2010 - 10:35:00 CEST
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