Jip J. Dekker
f2a1c4e389
git-subtree-dir: software/mza git-subtree-split: f970a59b177c13ca3dd8aaef8cc6681d83b7e813
49 lines
1.2 KiB
MiniZinc
49 lines
1.2 KiB
MiniZinc
% RUNS ON mzn20_fd
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% RUNS ON mzn-fzn_fd
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% RUNS ON mzn20_fd_linear
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% RUNS ON mzn20_mip
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%------------------------------------------------------------------------------%
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% The classical 0/1 multidimensional knapsack problem.
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%
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% There is a knapsack with m different capacity constraints and n items with
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% profits and weights. The goal is to maximise the total profit of the items
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% in the knapsack while not violating any of the capacity constraints.
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%------------------------------------------------------------------------------%
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int: n;
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int: m;
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array[1..n] of int: Profits;
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array[1..n,1..m] of int: Weights;
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array[1..m] of int: Capacities;
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array[1..n] of var 0..1: x;
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constraint
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forall(i in 1..m) (
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sum([Weights[j,i] * x[j] | j in 1..n]) <= Capacities[i]
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);
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solve maximize
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sum([x[j] * Profits[j] | j in 1..n]);
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output [ "multidimknapsack_simple " ] ++
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[ show(x[i]) ++ if i = n then "\n" else " " endif | i in 1..n ];
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%------------------------------------------------------------------------------%
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% data
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n = 5;
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m = 3;
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Profits = [5,6,3,7,4];
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Capacities = [5,10,15];
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Weights = [| 2, 3, 2
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| 1, 4, 4
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| 1, 2, 5
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| 3, 2, 3
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| 1, 3, 5 |];
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