Lines Matching defs:with
6 % in compliance with the License. You may obtain a copy of the License
23 \chapter{Getting started with Interval Constraints}
28 works with both integer and real interval variables.
71 that support optimization in conjunction with any \eclipse{} solver.
79 \item Create the variables with their initial domains
85 The idea is to associate a digit (0-9) with each letter so that the
95 % Assign a finite domain with each letter - S, E, N, D, M, O, R, Y -
304 Figure~\ref{general-constraints}. These constraints can be used with either
374 Compare with the corresponding bounds consistency constraint:
482 in an expression context and as such should provide a version with an extra
612 Consider as an example the case of 5 variables with domains \texttt{1..4}.
682 constraints such as \texttt{cumulative/4}, but with increasing cost to do
697 can be colocated with another and that products are distinguished by numeric
712 can be defined in {\eclipse}. They are different solutions with different
764 corresponding elements at a specific index of two lists, with one
796 with all currently imposed constraints.
892 integer value associated with each colour. This allows the readability of the code
896 And a structure that represents the bin itself, with its colour,
907 structures with {\em inherited} fields can be found in
925 the same, but with the bins in a different order).
937 is awkward to model the problem with a fixed set of variables.
942 each one with a - larger - fixed number of bins,
945 The predicate \verb0bin_setup/20, to generate a list of bins with appropriate
947 First it tries to match the (remaining) demand with zero,
1133 Fill the circles in the following diagram with the numbers 1 through 19 such