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 | Predicate weighted_maximum/3 |
:- use_module(library(clpb)).
[multi]weighted_maximum(+Weights,
+Vs, -Maximum)sum(Weight_i*V_i) over
all admissible assignments. On backtracking, all admissible assignments
that attain the optimum are generated.
This predicate can also be used to minimize a linear Boolean program, since negative integers can appear in Weights.
Example:
?- sat(A#B), weighted_maximum([1,2,1], [A,B,C], Maximum). A = 0, B = 1, C = 1, Maximum = 3.
0 
Other example :
%:- use_module(library(clpfd)).
%If you have version < v9.1
%Workaround
weighted_maximum(Weights, Vars, Max) :- scalar_product(Weights, Vars, #=, Sum), Max #= Sum.
A in 0..1, B in 0..1, C in 0..1, A #\= B, A #= C, weighted_maximum([1,2,1], [A,B,C], Maximum), labeling([], [A,B,C,Maximum]).
A = C, C = 0, B = 1, Maximum = 2 ;
A = C, C = 1, B = 0, Maximum = 2.