Remove tests giving invalid results
This commit is contained in:
parent
d1f017fc6f
commit
0b19327be7
@ -9,11 +9,6 @@
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"stack-cuttingstock","stack-cuttingstock/stack-cutstock-cumu.mzn","stack-cuttingstock/d8.dzn"
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"stack-cuttingstock","stack-cuttingstock/stack-cutstock-cumu.mzn","stack-cuttingstock/d5.dzn"
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"stack-cuttingstock","stack-cuttingstock/stack-cutstock-cumu.mzn","stack-cuttingstock/d7.dzn"
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"zephyrus","zephyrus/zephyrus.mzn","zephyrus/12__8__6__3.dzn"
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"zephyrus","zephyrus/zephyrus.mzn","zephyrus/14__8__6__3.dzn"
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"zephyrus","zephyrus/zephyrus.mzn","zephyrus/14__6__8__3.dzn"
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"zephyrus","zephyrus/zephyrus.mzn","zephyrus/12__6__8__3.dzn"
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"zephyrus","zephyrus/zephyrus.mzn","zephyrus/14__10__8__3.dzn"
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"depot-placement","depot-placement/depot_placement.mzn","depot-placement/ts225_5.dzn"
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"depot-placement","depot-placement/depot_placement.mzn","depot-placement/u159_4.dzn"
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"depot-placement","depot-placement/depot_placement.mzn","depot-placement/att48_5.dzn"
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@ -38,21 +33,6 @@
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"depot-placement","depot-placement/depot_placement.mzn","depot-placement/ulysses16_5.dzn"
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"depot-placement","depot-placement/depot_placement.mzn","depot-placement/ts225_6.dzn"
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"depot-placement","depot-placement/depot_placement.mzn","depot-placement/ulysses22_6.dzn"
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"train","train/train.mzn","train/instance.15.dzn"
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"train","train/train.mzn","train/instance.2.dzn"
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"train","train/train.mzn","train/instance.3.dzn"
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"train","train/train.mzn","train/instance.6.dzn"
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"train","train/train.mzn","train/instance.12.dzn"
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"train","train/train.mzn","train/instance.5.dzn"
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"train","train/train.mzn","train/instance.1.dzn"
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"train","train/train.mzn","train/instance.13.dzn"
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"train","train/train.mzn","train/instance.4.dzn"
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"train","train/train.mzn","train/instance.9.dzn"
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"train","train/train.mzn","train/instance.14.dzn"
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"train","train/train.mzn","train/instance.8.dzn"
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"train","train/train.mzn","train/instance.7.dzn"
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"train","train/train.mzn","train/instance.11.dzn"
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"train","train/train.mzn","train/instance.10.dzn"
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"triangular","triangular/triangular.mzn","triangular/n10.dzn"
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"triangular","triangular/triangular.mzn","triangular/n23.dzn"
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"triangular","triangular/triangular.mzn","triangular/n37.dzn"
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@ -152,11 +132,6 @@
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"kidney-exchange","kidney-exchange/ccmcp.mzn","kidney-exchange/3_20_0.30_5.dzn"
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"kidney-exchange","kidney-exchange/ccmcp.mzn","kidney-exchange/3_20_0.25_2.dzn"
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"kidney-exchange","kidney-exchange/ccmcp.mzn","kidney-exchange/3_25_0.20_3.dzn"
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"median-string","median-string/median_string_dp.mzn","median-string/p2_2_20-2.dzn"
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"median-string","median-string/median_string_dp.mzn","median-string/p1_15_20-1.dzn"
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"median-string","median-string/median_string_dp.mzn","median-string/p2_10_8-3.dzn"
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"median-string","median-string/median_string_dp.mzn","median-string/p2_10_8-0.dzn"
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"median-string","median-string/median_string_dp.mzn","median-string/p2_4_20-0.dzn"
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"road-cons","road-cons/road_naive.mzn","road-cons/road_33.dzn"
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"road-cons","road-cons/road_naive.mzn","road-cons/road_26.dzn"
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"road-cons","road-cons/road_naive.mzn","road-cons/road_25.dzn"
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@ -1,81 +0,0 @@
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%------------------------------------------------------------------------------
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% Parameters
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int: num_strings;
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int: max_length_strings;
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int: max_char;
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int: max_length_median;
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array [1..num_strings, 1..max_length_strings] of int: strings;
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array [1..num_strings] of int: str_length;
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%------------------------------------------------------------------------------
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% Variables
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array [1..max_length_strings] of var 0..max_char: median;
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array [1..num_strings] of var 0..2*max_length_strings: distances;
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int: obj_ub = num_strings * 2 * max_length_strings;
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var 0..obj_ub: objective;
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%------------------------------------------------------------------------------
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% Predicates
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predicate lcs_global(array[int] of var int: S1, array[int] of var int: S2, var int: ED) =
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let { int: l1 = min(index_set(S1)) - 1;
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int: l2 = min(index_set(S2)) - 1;
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int: u1 = max(index_set(S1));
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int: u2 = max(index_set(S2));
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array[l1..u1,l2..u2] of var 0..u1+u2: T; } in
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T[l1,l2] = 0 /\
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T[u1,u2] = ED /\
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forall(i in l1+1..u1, j in l2+1..u2)
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(T[i,j] >= 0 /\ T[i,j] <= i+j) /\
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forall(j in l2+1..u2)(T[l1,j] = j-l2) /\
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forall(i in l1+1..u1)(T[i,l2] = i-l1) /\
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forall(i in l1+1..u1, j in l2+1..u2)
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(T[i,j] = if S1[i] = S2[j] then
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T[i-1,j-1]
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else
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if S1[i] = 0 then
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T[i-1,j]
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else
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if S2[j] = 0 then
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T[i,j-1]
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else
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min([T[i-1,j]+1,T[i,j-1]+1])
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endif
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endif
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endif
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);
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%------------------------------------------------------------------------------
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% Constraints
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constraint forall(i in 1..num_strings)(
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lcs_global([strings[i,j] | j in 1..max_length_strings], median, distances[i])
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);
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constraint forall(i in max_length_median+1..max_length_strings)(
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median[i] = 0
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);
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constraint objective = sum(i in 1..num_strings)(distances[i]);
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%------------------------------------------------------------------------------
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% Solve item
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solve
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:: int_search(median, input_order, indomain_min, complete)
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minimize objective;
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%------------------------------------------------------------------------------
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% Output
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output [
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"median = \(median);\n",
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"objective = \(objective);\n"
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];
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@ -1,6 +0,0 @@
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num_strings=15;
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max_length_strings=20;
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max_length_median=20;
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max_char=4;
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strings=[|2,1,2,1,1,1,2,1,2,2,1,1,1,2,1,1,2,2,1,1|2,1,1,1,1,2,1,1,1,2,1,1,2,1,1,2,1,1,2,1|1,1,1,3,1,1,1,1,1,2,1,2,2,2,2,1,1,1,1,1|2,1,2,1,2,1,1,1,2,2,1,2,3,1,1,2,1,1,1,1|1,1,1,1,1,1,1,2,1,1,2,2,1,2,1,1,1,3,2,1|1,1,2,1,1,1,1,1,1,2,1,2,1,2,1,1,1,1,1,1|1,1,1,2,2,1,1,2,1,2,1,1,1,2,1,2,1,1,1,2|2,1,2,1,1,1,2,1,1,1,2,1,1,1,2,1,2,1,1,1|2,1,1,1,1,2,1,1,2,1,1,1,1,1,1,2,2,2,1,1|2,1,2,2,2,1,1,1,1,1,1,1,1,1,1,2,3,1,2,1|1,3,1,2,1,1,3,1,1,1,1,2,1,2,1,1,1,2,1,2|1,1,2,1,3,1,1,1,1,1,1,1,1,1,2,1,2,1,1,1|1,1,1,1,1,1,2,1,1,2,1,1,2,1,1,1,2,2,1,3|1,2,1,2,1,1,2,2,3,1,2,1,1,2,1,1,1,1,2,2|2,1,1,2,2,2,1,2,2,1,1,1,2,2,1,1,1,1,2,1|];
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str_length=[20,20,20,20,20,20,20,20,20,20,20,20,20,20,20];
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@ -1,6 +0,0 @@
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num_strings=10;
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max_length_strings=8;
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max_length_median=8;
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max_char=4;
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strings=[|4,3,4,2,0,0,0,0|2,1,2,4,1,4,0,0|4,0,0,0,0,0,0,0|1,4,3,2,2,3,2,0|3,3,2,3,1,2,0,0|3,0,0,0,0,0,0,0|1,4,3,2,0,0,0,0|1,3,3,3,4,2,3,0|2,1,2,0,0,0,0,0|1,2,3,4,3,0,0,0|];
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str_length=[4,6,1,7,6,1,4,7,3,5];
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@ -1,6 +0,0 @@
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num_strings=10;
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max_length_strings=8;
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max_length_median=8;
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max_char=4;
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strings=[|3,1,2,3,4,1,1,0|1,4,1,4,1,2,0,0|1,3,1,0,0,0,0,0|3,0,0,0,0,0,0,0|4,3,0,0,0,0,0,0|1,4,4,2,3,0,0,0|4,3,2,2,1,3,1,1|2,0,0,0,0,0,0,0|3,3,2,3,4,3,0,0|2,3,4,1,1,2,2,0|];
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str_length=[7,6,3,1,2,5,8,1,6,7];
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@ -1,6 +0,0 @@
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num_strings=2;
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max_length_strings=20;
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max_length_median=20;
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max_char=4;
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strings=[|4,4,4,1,4,3,1,3,4,1,0,0,0,0,0,0,0,0,0,0|2,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0|];
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str_length=[10,2];
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@ -1,6 +0,0 @@
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num_strings=4;
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max_length_strings=20;
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max_length_median=20;
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max_char=4;
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strings=[|4,4,3,1,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0|2,3,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0|4,4,4,4,4,3,4,4,2,0,0,0,0,0,0,0,0,0,0,0|2,3,1,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0|];
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str_length=[5,3,9,3];
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@ -1,12 +0,0 @@
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n = 3;
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m = 3;
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maxTime = 1140;
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delayTime = 5;
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delayTrain = 2;
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delayDuration = 5;
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distance = [5,5];
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passengerStart = [0,0,0];
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passengerFlow = [0,10,0];
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scheduledArrival = [|0,5,13, |0,15,23, |0,25,33|];
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scheduledDeparture = [|0,8,16, |10,18,26, |20,28,36|];
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capacity = 500;
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@ -1,12 +0,0 @@
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n = 5;
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m = 5;
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maxTime = 1140;
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delayTime = 15;
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delayTrain = 2;
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delayDuration = 20;
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distance = [5,5,5,5];
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passengerStart = [0,0,6,14,0];
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passengerFlow = [0,10,10,10,0];
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scheduledArrival = [|0,5,13,21,29, |0,15,23,31,39, |0,25,33,41,49, |0,35,43,51,59, |0,45,53,61,69|];
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scheduledDeparture = [|0,8,16,24,32, |10,18,26,34,42, |20,28,36,44,52, |30,38,46,54,62, |40,48,56,64,72|];
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capacity = 500;
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@ -1,12 +0,0 @@
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n = 5;
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m = 5;
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maxTime = 1140;
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delayTime = 38;
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delayTrain = 2;
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delayDuration = 5;
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distance = [5,5,5,5];
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passengerStart = [0,0,6,14,0];
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passengerFlow = [0,10,10,10,0];
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scheduledArrival = [|0,5,13,21,29, |0,15,23,31,39, |0,25,33,41,49, |0,35,43,51,59, |0,45,53,61,69|];
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scheduledDeparture = [|0,8,16,24,32, |10,18,26,34,42, |20,28,36,44,52, |30,38,46,54,62, |40,48,56,64,72|];
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capacity = 500;
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@ -1,12 +0,0 @@
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n = 5;
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m = 5;
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maxTime = 1140;
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delayTime = 25;
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delayTrain = 2;
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delayDuration = 5;
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distance = [5,5,5,5];
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passengerStart = [0,0,6,14,0];
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passengerFlow = [0,10,10,10,0];
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scheduledArrival = [|0,5,13,21,29, |0,15,23,31,39, |0,25,33,41,49, |0,35,43,51,59, |0,45,53,61,69|];
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scheduledDeparture = [|0,8,16,24,32, |10,18,26,34,42, |20,28,36,44,52, |30,38,46,54,62, |40,48,56,64,72|];
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capacity = 500;
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@ -1,12 +0,0 @@
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n = 5;
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m = 5;
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maxTime = 1140;
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delayTime = 25;
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delayTrain = 2;
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delayDuration = 10;
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distance = [5,5,5,5];
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passengerStart = [0,0,6,14,0];
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passengerFlow = [0,10,10,10,0];
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scheduledArrival = [|0,5,13,21,29, |0,15,23,31,39, |0,25,33,41,49, |0,35,43,51,59, |0,45,53,61,69|];
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scheduledDeparture = [|0,8,16,24,32, |10,18,26,34,42, |20,28,36,44,52, |30,38,46,54,62, |40,48,56,64,72|];
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capacity = 500;
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@ -1,12 +0,0 @@
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n = 5;
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m = 5;
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maxTime = 1140;
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delayTime = 25;
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delayTrain = 2;
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delayDuration = 15;
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distance = [5,5,5,5];
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passengerStart = [0,0,6,14,0];
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passengerFlow = [0,10,10,10,0];
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scheduledArrival = [|0,5,13,21,29, |0,15,23,31,39, |0,25,33,41,49, |0,35,43,51,59, |0,45,53,61,69|];
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scheduledDeparture = [|0,8,16,24,32, |10,18,26,34,42, |20,28,36,44,52, |30,38,46,54,62, |40,48,56,64,72|];
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capacity = 500;
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@ -1,12 +0,0 @@
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n = 5;
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m = 5;
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maxTime = 1140;
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delayTime = 25;
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delayTrain = 2;
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delayDuration = 20;
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distance = [5,5,5,5];
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passengerStart = [0,0,6,14,0];
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passengerFlow = [0,10,10,10,0];
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scheduledArrival = [|0,5,13,21,29, |0,15,23,31,39, |0,25,33,41,49, |0,35,43,51,59, |0,45,53,61,69|];
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scheduledDeparture = [|0,8,16,24,32, |10,18,26,34,42, |20,28,36,44,52, |30,38,46,54,62, |40,48,56,64,72|];
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capacity = 500;
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@ -1,12 +0,0 @@
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n = 5;
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m = 5;
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maxTime = 1140;
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delayTime = 5;
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delayTrain = 2;
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delayDuration = 5;
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distance = [5,5,5,5];
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passengerStart = [0,0,6,14,0];
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passengerFlow = [0,10,10,10,0];
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scheduledArrival = [|0,5,13,21,29, |0,15,23,31,39, |0,25,33,41,49, |0,35,43,51,59, |0,45,53,61,69|];
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scheduledDeparture = [|0,8,16,24,32, |10,18,26,34,42, |20,28,36,44,52, |30,38,46,54,62, |40,48,56,64,72|];
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capacity = 500;
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@ -1,12 +0,0 @@
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n = 5;
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m = 5;
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maxTime = 1140;
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delayTime = 5;
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delayTrain = 2;
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delayDuration = 10;
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distance = [5,5,5,5];
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passengerStart = [0,0,6,14,0];
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passengerFlow = [0,10,10,10,0];
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scheduledArrival = [|0,5,13,21,29, |0,15,23,31,39, |0,25,33,41,49, |0,35,43,51,59, |0,45,53,61,69|];
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scheduledDeparture = [|0,8,16,24,32, |10,18,26,34,42, |20,28,36,44,52, |30,38,46,54,62, |40,48,56,64,72|];
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capacity = 500;
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@ -1,12 +0,0 @@
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n = 5;
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m = 5;
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maxTime = 1140;
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delayTime = 5;
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delayTrain = 2;
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delayDuration = 15;
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distance = [5,5,5,5];
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passengerStart = [0,0,6,14,0];
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passengerFlow = [0,10,10,10,0];
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scheduledArrival = [|0,5,13,21,29, |0,15,23,31,39, |0,25,33,41,49, |0,35,43,51,59, |0,45,53,61,69|];
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scheduledDeparture = [|0,8,16,24,32, |10,18,26,34,42, |20,28,36,44,52, |30,38,46,54,62, |40,48,56,64,72|];
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capacity = 500;
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@ -1,12 +0,0 @@
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n = 5;
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m = 5;
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maxTime = 1140;
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delayTime = 5;
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delayTrain = 2;
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delayDuration = 20;
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distance = [5,5,5,5];
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passengerStart = [0,0,6,14,0];
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passengerFlow = [0,10,10,10,0];
|
||||
scheduledArrival = [|0,5,13,21,29, |0,15,23,31,39, |0,25,33,41,49, |0,35,43,51,59, |0,45,53,61,69|];
|
||||
scheduledDeparture = [|0,8,16,24,32, |10,18,26,34,42, |20,28,36,44,52, |30,38,46,54,62, |40,48,56,64,72|];
|
||||
capacity = 500;
|
||||
@ -1,12 +0,0 @@
|
||||
n = 4;
|
||||
m = 4;
|
||||
maxTime = 1140;
|
||||
delayTime = 15;
|
||||
delayTrain = 2;
|
||||
delayDuration = 5;
|
||||
distance = [5,5,5];
|
||||
passengerStart = [0,0,6,0];
|
||||
passengerFlow = [0,10,10,0];
|
||||
scheduledArrival = [|0,5,13,21, |0,15,23,31, |0,25,33,41, |0,35,43,51|];
|
||||
scheduledDeparture = [|0,8,16,24, |10,18,26,34, |20,28,36,44, |30,38,46,54|];
|
||||
capacity = 500;
|
||||
@ -1,12 +0,0 @@
|
||||
n = 5;
|
||||
m = 5;
|
||||
maxTime = 1140;
|
||||
delayTime = 15;
|
||||
delayTrain = 2;
|
||||
delayDuration = 5;
|
||||
distance = [5,5,5,5];
|
||||
passengerStart = [0,0,6,14,0];
|
||||
passengerFlow = [0,10,10,10,0];
|
||||
scheduledArrival = [|0,5,13,21,29, |0,15,23,31,39, |0,25,33,41,49, |0,35,43,51,59, |0,45,53,61,69|];
|
||||
scheduledDeparture = [|0,8,16,24,32, |10,18,26,34,42, |20,28,36,44,52, |30,38,46,54,62, |40,48,56,64,72|];
|
||||
capacity = 500;
|
||||
@ -1,12 +0,0 @@
|
||||
n = 5;
|
||||
m = 5;
|
||||
maxTime = 1140;
|
||||
delayTime = 15;
|
||||
delayTrain = 2;
|
||||
delayDuration = 10;
|
||||
distance = [5,5,5,5];
|
||||
passengerStart = [0,0,6,14,0];
|
||||
passengerFlow = [0,10,10,10,0];
|
||||
scheduledArrival = [|0,5,13,21,29, |0,15,23,31,39, |0,25,33,41,49, |0,35,43,51,59, |0,45,53,61,69|];
|
||||
scheduledDeparture = [|0,8,16,24,32, |10,18,26,34,42, |20,28,36,44,52, |30,38,46,54,62, |40,48,56,64,72|];
|
||||
capacity = 500;
|
||||
@ -1,12 +0,0 @@
|
||||
n = 5;
|
||||
m = 5;
|
||||
maxTime = 1140;
|
||||
delayTime = 15;
|
||||
delayTrain = 2;
|
||||
delayDuration = 15;
|
||||
distance = [5,5,5,5];
|
||||
passengerStart = [0,0,6,14,0];
|
||||
passengerFlow = [0,10,10,10,0];
|
||||
scheduledArrival = [|0,5,13,21,29, |0,15,23,31,39, |0,25,33,41,49, |0,35,43,51,59, |0,45,53,61,69|];
|
||||
scheduledDeparture = [|0,8,16,24,32, |10,18,26,34,42, |20,28,36,44,52, |30,38,46,54,62, |40,48,56,64,72|];
|
||||
capacity = 500;
|
||||
@ -1,176 +0,0 @@
|
||||
%----------------------------------------------------------------------------%
|
||||
%----------------------------------------------------------------------------%
|
||||
%
|
||||
% We have n trains moving along a single track with m stations. There is a
|
||||
% non-zero constant flow of passengers arriving at all but the first and last
|
||||
% station who wish to travel to the final station. Trains are originally
|
||||
% scheduled so that they collect the passengers and drop them at the final
|
||||
% station. To this original schedule a disruption is introduced whereby a train
|
||||
% is delayed. Each of the trains (at the time of the delay) has knowledge of the
|
||||
% duration of the delay. The objective is to reschedule the trains to minimize
|
||||
% the average travel time of the passengers. Trains are not able to overtake
|
||||
% preceding trains, however they do have the option to
|
||||
% skip a station and wait longer at a station to collect more passengers.
|
||||
|
||||
%----------------------------------------------------------------------------%
|
||||
%----------------------------------------------------------------------------%
|
||||
|
||||
%include "globals.mzn";
|
||||
|
||||
int : n;
|
||||
int : m;
|
||||
|
||||
int : maxTime;
|
||||
|
||||
0..maxTime : delayTime;
|
||||
1..n : delayTrain;
|
||||
0..maxTime : delayDuration;
|
||||
|
||||
array [1..m-1] of 0..maxTime : distance;
|
||||
|
||||
array [1..n, 1..m] of 0..maxTime : scheduledArrival;
|
||||
array [1..n, 1..m] of 0..maxTime : scheduledDeparture;
|
||||
|
||||
array [1..m] of 0..maxTime : passengerStart;
|
||||
array [1..m] of 0..maxTime : passengerStop = [scheduledDeparture[n,j] | j in 1..m];
|
||||
array [1..m] of int : passengerFlow;
|
||||
|
||||
array [1..n, 1..m] of var 0..maxTime : departure;
|
||||
array [1..n, 1..m] of var 0..maxTime : arrival;
|
||||
|
||||
array [1..n] of var 0..maxTime : finalArrival = [ arrival[i,m] | i in 1..n ];
|
||||
|
||||
array [1..n, 1..m] of var 0..maxTime : sigmaLower;
|
||||
array [1..n, 1..m] of var 0..maxTime : sigmaUpper;
|
||||
|
||||
int : capacity;
|
||||
|
||||
array [1..n, 1..m] of var 0..capacity : collect;
|
||||
array [1..n, 1..m] of var 0..capacity : load;
|
||||
|
||||
% All trains "arrive" at the first station at time 0.
|
||||
constraint forall (i in 1..n)
|
||||
(arrival[i,1] = 0);
|
||||
% ... and "depart" from the last station as soon as they arrive there.
|
||||
constraint forall (i in 1..n)
|
||||
(departure[i,m] = arrival[i,m]);
|
||||
|
||||
% Before the delay, everything runs to schedule.
|
||||
constraint forall (i in 1..n, j in 1..m-1)
|
||||
(if scheduledDeparture[i,j] <= delayTime
|
||||
then departure[i,j] = scheduledDeparture[i,j]
|
||||
else true
|
||||
endif);
|
||||
|
||||
% If the train is in motion, then the arrival of the
|
||||
% delayed train is at least the departure time at the previous station
|
||||
% plus the ordinary travel time plus the duration of the delay.
|
||||
int : destinationWhenDelayed = min([j | j in 1..m where scheduledDeparture[delayTrain,j] > delayTime]);
|
||||
constraint if destinationWhenDelayed > 1
|
||||
then if delayTime < scheduledDeparture[delayTrain,destinationWhenDelayed-1] + distance[destinationWhenDelayed-1]
|
||||
then arrival[delayTrain,destinationWhenDelayed] >=
|
||||
departure[delayTrain,destinationWhenDelayed-1] + delayDuration + distance[destinationWhenDelayed-1]
|
||||
else true
|
||||
endif
|
||||
else true
|
||||
endif;
|
||||
% The train's next departure is at least the delay time plus the delay
|
||||
% duration.
|
||||
constraint departure[delayTrain, destinationWhenDelayed] >= delayTime + delayDuration;
|
||||
|
||||
% Trains depart after they arrive.
|
||||
constraint forall (i in 1..n, j in 1..m)
|
||||
(departure[i,j] >= arrival[i,j]);
|
||||
|
||||
% Trains never leave earlier than scheduled.
|
||||
constraint forall (i in 1..n, j in 1..m-1)
|
||||
(departure[i,j] >= scheduledDeparture[i,j]);
|
||||
|
||||
% There is a minimum travel time between stations.
|
||||
constraint forall (i in 1..n, j in 1..m-1)
|
||||
(arrival[i,j+1] >= departure[i,j] + distance[j]);
|
||||
|
||||
% At station 1, trains leave in order.
|
||||
constraint forall (i in 1..n-1)
|
||||
(departure[i,1] < departure[i+1,1]);
|
||||
% At most one train dwelling at a station at a given time.
|
||||
constraint forall (i in 1..n-1, j in 2..m-1)
|
||||
(departure[i,j] <= arrival[i+1,j]-2);
|
||||
|
||||
% The sigma values partition time at each station.
|
||||
constraint forall (i in 1..n, j in 1..m)
|
||||
(sigmaLower[i,j] <= sigmaUpper[i,j]);
|
||||
|
||||
% For the first and last trains, the sigma values are equal to the
|
||||
% extreme times of passenger arrivals.
|
||||
constraint forall (j in 2..m-1)
|
||||
((sigmaLower[1,j] = passengerStart[j])
|
||||
/\ (sigmaUpper[n,j] = scheduledDeparture[n,j]));
|
||||
% The sigma values join together.
|
||||
constraint forall (i in 1..n-1, j in 1..m)
|
||||
(sigmaUpper[i,j] = sigmaLower[i+1,j]);
|
||||
|
||||
% You can't pick up people after you leave.
|
||||
constraint forall (i in 1..n-1, j in 1..m-1)
|
||||
(sigmaUpper[i,j] <= departure[i,j]);
|
||||
constraint forall (j in 1..m-1)
|
||||
(sigmaUpper[n,j] <= departure[n,j]);
|
||||
|
||||
% Defines collect and load variables.
|
||||
constraint forall (i in 1..n, j in 1..m)
|
||||
(collect[i,j] = (sigmaUpper[i,j]-sigmaLower[i,j])*passengerFlow[j]);
|
||||
|
||||
constraint forall (i in 1..n) (load[i,1] = collect[i,1]);
|
||||
constraint forall (i in 1..n, j in 2..m)
|
||||
(load[i,j] = load[i,j-1] + collect[i,j]);
|
||||
|
||||
% If a train picks anyone up, then it must pick
|
||||
% everyone up (until it gets full).
|
||||
constraint forall (i in 1..n, j in 1..m-1)
|
||||
(sigmaUpper[i,j] > sigmaLower[i,j] ->
|
||||
((sigmaUpper[i,j] = departure[i,j]) \/
|
||||
(sigmaUpper[i,j] = scheduledDeparture[n,j]) \/
|
||||
(load[i,j] + bool2int(sigmaUpper[i,j] < scheduledDeparture[n,j])*passengerFlow[j] > capacity)));
|
||||
|
||||
% Boarding time.
|
||||
constraint forall (i in 1..n, j in 2..m)
|
||||
(((capacity-load[i,j-1] < 100) -> (collect[i,j] <= dwell[i,j]*20)) /\
|
||||
((capacity-load[i,j-1] >= 100) -> (collect[i,j] <= dwell[i,j]*50)));
|
||||
% (Redundant for j>=2 (but necessary for j=1))
|
||||
constraint forall (i in 1..n, j in 1..m)
|
||||
(collect[i,j] <= (departure[i,j]-arrival[i,j])*50);
|
||||
|
||||
array [1..n, 1..m] of var 0..maxTime : dwell;
|
||||
constraint forall (i in 1..n, j in 1..m) (dwell[i,j] = departure[i,j] - arrival[i,j]);
|
||||
|
||||
int: objective_min = lb(sum(i in 1..n)(load[i,m]*arrival[i,m]));
|
||||
int: objective_max = ub(sum(i in 1..n)(load[i,m]*arrival[i,m]));
|
||||
var objective_min..objective_max: objective = sum(i in 1..n)(load[i,m]*arrival[i,m]);
|
||||
|
||||
solve
|
||||
:: seq_search([
|
||||
int_search(
|
||||
[arrival[i,m-j+1] | j in 1..m, i in 1..n] ++
|
||||
[departure[i,m-j+1] | j in 1..m, i in 1..n] ++
|
||||
[sigmaUpper[i,m-j+1] | j in 1..m, i in 1..n] ++
|
||||
[sigmaLower[i,m-j+1] | j in 1..m, i in 1..n],
|
||||
input_order, indomain_min, complete
|
||||
),
|
||||
int_search(
|
||||
array1d(1..n*m, collect) ++ array1d(1..n*m, load) ++ array1d(1..n*m, dwell),
|
||||
first_fail, indomain_min, complete
|
||||
)
|
||||
])
|
||||
minimize objective;
|
||||
|
||||
output [
|
||||
"arrival = array2d(1..", show(n), ", 1..", show(m), ", ", show(arrival), ");\n",
|
||||
"departure = array2d(1..", show(n), ", 1..", show(m), ", ", show(departure), ");\n",
|
||||
"sigmaLower = array2d(1..", show(n), ", 1..", show(m), ", ", show(sigmaLower), ");\n",
|
||||
"sigmaUpper = array2d(1..", show(n), ", 1..", show(m), ", ", show(sigmaUpper), ");\n",
|
||||
"collect = array2d(1..", show(n), ", 1..", show(m), ", ", show(collect), ");\n",
|
||||
"load = array2d(1..", show(n), ", 1..", show(m), ", ", show(load), ");\n",
|
||||
"dwell = array2d(1..", show(n), ", 1..", show(m), ", ", show(dwell), ");\n",
|
||||
"constraint objective = ", show(objective), ";\n"
|
||||
];
|
||||
|
||||
@ -1,18 +0,0 @@
|
||||
comps = 1..4;
|
||||
ports = 1..4;
|
||||
multi_provide_ports = 1..5;
|
||||
locations = 1..48;
|
||||
resources = 1..1;
|
||||
requirement_port_nums = [|
|
||||
0,8,0,0|0,17,0,0|6,0,0,0|0,0,0,0|];
|
||||
provide_port_nums = [|
|
||||
-1,0,0,0,0|0,-1,-1,0,0|0,0,0,-1,0|0,0,0,0,3|];
|
||||
conflicts = [|
|
||||
false,false,false,false|false,false,true,false|false,false,false,false|false,false,false,false|];
|
||||
multi_provides = [|
|
||||
false,false,false,true|false,false,false,true|false,false,true,false|false,true,false,false|true,false,false,false|];
|
||||
costs = [260, 260, 260, 260, 260, 260, 260, 260, 260, 260, 260, 260, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 520, 520, 520, 520, 520, 520, 520, 520, 520, 520, 520, 520];
|
||||
resource_provisions = [|
|
||||
8052|8052|8052|8052|8052|8052|8052|8052|8052|8052|8052|8052|4026|4026|4026|4026|4026|4026|4026|4026|4026|4026|4026|4026|1825|1825|1825|1825|1825|1825|1825|1825|1825|1825|1825|1825|16104|16104|16104|16104|16104|16104|16104|16104|16104|16104|16104|16104|];
|
||||
resource_consumptions = [|
|
||||
512|64|512|512|];
|
||||
@ -1,18 +0,0 @@
|
||||
comps = 1..4;
|
||||
ports = 1..4;
|
||||
multi_provide_ports = 1..5;
|
||||
locations = 1..48;
|
||||
resources = 1..1;
|
||||
requirement_port_nums = [|
|
||||
0,6,0,0|0,13,0,0|8,0,0,0|0,0,0,0|];
|
||||
provide_port_nums = [|
|
||||
-1,0,0,0,0|0,-1,-1,0,0|0,0,0,-1,0|0,0,0,0,3|];
|
||||
conflicts = [|
|
||||
false,false,false,false|false,false,true,false|false,false,false,false|false,false,false,false|];
|
||||
multi_provides = [|
|
||||
false,false,false,true|false,false,false,true|false,false,true,false|false,true,false,false|true,false,false,false|];
|
||||
costs = [260, 260, 260, 260, 260, 260, 260, 260, 260, 260, 260, 260, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 520, 520, 520, 520, 520, 520, 520, 520, 520, 520, 520, 520];
|
||||
resource_provisions = [|
|
||||
8052|8052|8052|8052|8052|8052|8052|8052|8052|8052|8052|8052|4026|4026|4026|4026|4026|4026|4026|4026|4026|4026|4026|4026|1825|1825|1825|1825|1825|1825|1825|1825|1825|1825|1825|1825|16104|16104|16104|16104|16104|16104|16104|16104|16104|16104|16104|16104|];
|
||||
resource_consumptions = [|
|
||||
512|64|512|512|];
|
||||
@ -1,18 +0,0 @@
|
||||
comps = 1..4;
|
||||
ports = 1..4;
|
||||
multi_provide_ports = 1..5;
|
||||
locations = 1..56;
|
||||
resources = 1..1;
|
||||
requirement_port_nums = [|
|
||||
0,8,0,0|0,17,0,0|10,0,0,0|0,0,0,0|];
|
||||
provide_port_nums = [|
|
||||
-1,0,0,0,0|0,-1,-1,0,0|0,0,0,-1,0|0,0,0,0,3|];
|
||||
conflicts = [|
|
||||
false,false,false,false|false,false,true,false|false,false,false,false|false,false,false,false|];
|
||||
multi_provides = [|
|
||||
false,false,false,true|false,false,false,true|false,false,true,false|false,true,false,false|true,false,false,false|];
|
||||
costs = [260, 260, 260, 260, 260, 260, 260, 260, 260, 260, 260, 260, 260, 260, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 520, 520, 520, 520, 520, 520, 520, 520, 520, 520, 520, 520, 520, 520];
|
||||
resource_provisions = [|
|
||||
8052|8052|8052|8052|8052|8052|8052|8052|8052|8052|8052|8052|8052|8052|4026|4026|4026|4026|4026|4026|4026|4026|4026|4026|4026|4026|4026|4026|1825|1825|1825|1825|1825|1825|1825|1825|1825|1825|1825|1825|1825|1825|16104|16104|16104|16104|16104|16104|16104|16104|16104|16104|16104|16104|16104|16104|];
|
||||
resource_consumptions = [|
|
||||
512|64|512|512|];
|
||||
@ -1,18 +0,0 @@
|
||||
comps = 1..4;
|
||||
ports = 1..4;
|
||||
multi_provide_ports = 1..5;
|
||||
locations = 1..56;
|
||||
resources = 1..1;
|
||||
requirement_port_nums = [|
|
||||
0,8,0,0|0,17,0,0|6,0,0,0|0,0,0,0|];
|
||||
provide_port_nums = [|
|
||||
-1,0,0,0,0|0,-1,-1,0,0|0,0,0,-1,0|0,0,0,0,3|];
|
||||
conflicts = [|
|
||||
false,false,false,false|false,false,true,false|false,false,false,false|false,false,false,false|];
|
||||
multi_provides = [|
|
||||
false,false,false,true|false,false,false,true|false,false,true,false|false,true,false,false|true,false,false,false|];
|
||||
costs = [260, 260, 260, 260, 260, 260, 260, 260, 260, 260, 260, 260, 260, 260, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 520, 520, 520, 520, 520, 520, 520, 520, 520, 520, 520, 520, 520, 520];
|
||||
resource_provisions = [|
|
||||
8052|8052|8052|8052|8052|8052|8052|8052|8052|8052|8052|8052|8052|8052|4026|4026|4026|4026|4026|4026|4026|4026|4026|4026|4026|4026|4026|4026|1825|1825|1825|1825|1825|1825|1825|1825|1825|1825|1825|1825|1825|1825|16104|16104|16104|16104|16104|16104|16104|16104|16104|16104|16104|16104|16104|16104|];
|
||||
resource_consumptions = [|
|
||||
512|64|512|512|];
|
||||
@ -1,18 +0,0 @@
|
||||
comps = 1..4;
|
||||
ports = 1..4;
|
||||
multi_provide_ports = 1..5;
|
||||
locations = 1..56;
|
||||
resources = 1..1;
|
||||
requirement_port_nums = [|
|
||||
0,6,0,0|0,13,0,0|8,0,0,0|0,0,0,0|];
|
||||
provide_port_nums = [|
|
||||
-1,0,0,0,0|0,-1,-1,0,0|0,0,0,-1,0|0,0,0,0,3|];
|
||||
conflicts = [|
|
||||
false,false,false,false|false,false,true,false|false,false,false,false|false,false,false,false|];
|
||||
multi_provides = [|
|
||||
false,false,false,true|false,false,false,true|false,false,true,false|false,true,false,false|true,false,false,false|];
|
||||
costs = [260, 260, 260, 260, 260, 260, 260, 260, 260, 260, 260, 260, 260, 260, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 130, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 65, 520, 520, 520, 520, 520, 520, 520, 520, 520, 520, 520, 520, 520, 520];
|
||||
resource_provisions = [|
|
||||
8052|8052|8052|8052|8052|8052|8052|8052|8052|8052|8052|8052|8052|8052|4026|4026|4026|4026|4026|4026|4026|4026|4026|4026|4026|4026|4026|4026|1825|1825|1825|1825|1825|1825|1825|1825|1825|1825|1825|1825|1825|1825|16104|16104|16104|16104|16104|16104|16104|16104|16104|16104|16104|16104|16104|16104|];
|
||||
resource_consumptions = [|
|
||||
512|64|512|512|];
|
||||
@ -1,266 +0,0 @@
|
||||
% Copyright (c) 2016, Jacopo Mauro. All rights reserved.
|
||||
% This file is licensed under the terms of the ISC License.
|
||||
|
||||
|
||||
% Please note that you will need to set the MiniZinc standard library
|
||||
% environment variable $MZN_STDLIB_PATH to share/minizinc to include
|
||||
% the MiniSearch builtins
|
||||
|
||||
include "lex_greatereq.mzn";
|
||||
include "lex_less.mzn";
|
||||
|
||||
int: MAX_INT = 4096;
|
||||
%%%%%%%%%%%%%%%%
|
||||
% Input parameters
|
||||
%%%%%%%%%%%%%%%%
|
||||
|
||||
% components
|
||||
set of int: comps;
|
||||
% ports
|
||||
set of int: ports;
|
||||
% multiple provide port
|
||||
set of int: multi_provide_ports;
|
||||
|
||||
% locations
|
||||
set of int: locations;
|
||||
% resources
|
||||
set of int: resources;
|
||||
|
||||
% map of components with their requirements number
|
||||
array[ comps, ports] of int: requirement_port_nums;
|
||||
% map of components with their provided multi-ports
|
||||
% -1 means infinite multi-port provider
|
||||
array[ comps, multi_provide_ports] of int: provide_port_nums;
|
||||
% map of components with their conflicts
|
||||
array[ comps, ports] of bool: conflicts;
|
||||
% map of multi-ports with their ports
|
||||
array[ multi_provide_ports, ports] of bool: multi_provides;
|
||||
|
||||
% map of location with their costs
|
||||
array[ locations ] of int: costs;
|
||||
% map of locations with the resouces they provide
|
||||
array[ locations, resources ] of int: resource_provisions;
|
||||
% map of components with the resources they consume
|
||||
array[ comps, resources ] of int: resource_consumptions;
|
||||
|
||||
%%%%%%%%%%%%%%%%
|
||||
% variables
|
||||
%%%%%%%%%%%%%%%%
|
||||
% bindings number
|
||||
array[ multi_provide_ports, ports, comps, comps] of var 0..MAX_INT: bindings;
|
||||
% components number
|
||||
array[ comps ] of var 0..MAX_INT: comps_num;
|
||||
% location to number of component map
|
||||
array[ locations, comps] of var 0..MAX_INT: comp_locations;
|
||||
|
||||
% total number of components
|
||||
var 0..MAX_INT: sum_comp;
|
||||
|
||||
%%%%%%%%%%%%%%%%
|
||||
% constraints (no location)
|
||||
%%%%%%%%%%%%%%%%
|
||||
|
||||
% bind the total number of components
|
||||
constraint sum_comp = sum( i in comps)(comps_num[i]);
|
||||
|
||||
% bindings 0 if the multiprovide does not provide port
|
||||
constraint forall(mport in multi_provide_ports, port in ports) (
|
||||
if multi_provides[mport,port]
|
||||
then true
|
||||
else forall(i in comps, j in comps) ( bindings[mport,port,i,j] = 0)
|
||||
endif
|
||||
);
|
||||
|
||||
% provides must be greater or equal to bindings & infinite provide port constraints
|
||||
constraint forall(mport in multi_provide_ports, pcomp in comps) (
|
||||
if provide_port_nums[pcomp,mport]=0
|
||||
then forall(port in ports, rcomp in comps) (
|
||||
bindings[mport,port,pcomp,rcomp] = 0
|
||||
)
|
||||
else
|
||||
if (provide_port_nums[pcomp,mport] = -1)
|
||||
then forall(port in ports, rcomp in comps) (
|
||||
(comps_num[pcomp] = 0) -> (bindings[mport,port,pcomp,rcomp]=0))
|
||||
else sum( port in ports, rcomp in comps)(
|
||||
bindings[mport,port,pcomp,rcomp] ) <= comps_num[pcomp] * provide_port_nums[pcomp,mport]
|
||||
endif
|
||||
endif
|
||||
);
|
||||
|
||||
% requires must be equal to bindings
|
||||
% note: here is possible to require also smaller than or equal
|
||||
constraint forall(port in ports, rcomp in comps) (
|
||||
sum( mport in multi_provide_ports, pcomp in comps)(
|
||||
bindings[mport,port,pcomp,rcomp] ) = comps_num[rcomp] * requirement_port_nums[rcomp,port]
|
||||
);
|
||||
|
||||
|
||||
% conflict constraints if component provide same port
|
||||
constraint forall(port in ports, pcomp in comps) (
|
||||
if (conflicts[pcomp,port] /\ exists(mport in multi_provide_ports) (
|
||||
(multi_provides[mport,port]) /\ provide_port_nums[pcomp,mport] != 0))
|
||||
then comps_num[pcomp] <= 1
|
||||
else true
|
||||
endif
|
||||
);
|
||||
|
||||
% conflict constraints
|
||||
constraint forall(port in ports, pcomp in comps, rcomp in comps) (
|
||||
if (conflicts[rcomp,port] /\ exists(mport in multi_provide_ports) (
|
||||
(multi_provides[mport,port]) /\ provide_port_nums[pcomp,mport] != 0))
|
||||
then comps_num[pcomp] > 0 -> comps_num[rcomp] = 0
|
||||
else true
|
||||
endif
|
||||
);
|
||||
|
||||
% unicity constraint
|
||||
% note that we require that a component does not
|
||||
% require more than one port provided by a
|
||||
% multiple provide port
|
||||
constraint forall(mport in multi_provide_ports, pcomp in comps, rcomp in comps) (
|
||||
let
|
||||
{ int: max_req = sum(port in ports) (
|
||||
if multi_provides[mport,port]
|
||||
then requirement_port_nums[rcomp,port]
|
||||
else 0
|
||||
endif
|
||||
)
|
||||
} in
|
||||
if pcomp = rcomp
|
||||
then
|
||||
( comps_num[pcomp] >= max_req ->
|
||||
sum(port in ports)(bindings[mport,port,pcomp,rcomp])
|
||||
<= max_req * (comps_num[rcomp] - 1))
|
||||
/\
|
||||
( comps_num[pcomp] < max_req ->
|
||||
forall (i in 1..max_req)( comps_num[pcomp] = i ->
|
||||
sum(port in ports)(bindings[mport,port,pcomp,rcomp]) <= i * (i-1) ))
|
||||
else
|
||||
( comps_num[pcomp] >= max_req ->
|
||||
sum(port in ports)(bindings[mport,port,pcomp,rcomp])
|
||||
<= max_req * comps_num[rcomp] )
|
||||
/\
|
||||
( comps_num[pcomp] < max_req ->
|
||||
forall (i in 0..max_req)( comps_num[pcomp] = i ->
|
||||
sum(port in ports)(bindings[mport,port,pcomp,rcomp]) <= i * comps_num[rcomp] ) )
|
||||
endif
|
||||
);
|
||||
|
||||
%%%%%%%%%%%%%%%%
|
||||
% constraints for deciding locations
|
||||
%%%%%%%%%%%%%%%%
|
||||
|
||||
% map location used or not used
|
||||
array[ locations ] of var 0..1: used_locations;
|
||||
constraint forall( l in locations)(
|
||||
sum(c in comps)(comp_locations[l,c]) = 0 <-> used_locations[l] = 0
|
||||
);
|
||||
|
||||
constraint forall( c in comps) (
|
||||
sum( l in locations) ( comp_locations[l,c]) = comps_num[c]
|
||||
);
|
||||
|
||||
|
||||
constraint forall( res in resources, loc in locations) (
|
||||
sum( comp in comps)( comp_locations[loc,comp] * resource_consumptions[comp,res] )
|
||||
<= resource_provisions[loc,res]
|
||||
);
|
||||
|
||||
% the number of locations can not be greater than the number of components
|
||||
% i.e, one component per location in the worst case
|
||||
constraint sum(i in locations) (used_locations[i]) <= sum_comp;
|
||||
|
||||
%------------------------------------------------------------------------------%
|
||||
% symmetry constraints (wrap in a unique predicate following minizinc specs
|
||||
|
||||
|
||||
constraint symmetry_breaking_constraint(
|
||||
%if location are equal then first location has more comps than the second
|
||||
%in lexicographically order (based on the cost)
|
||||
forall( l1 in locations, l2 in locations)(
|
||||
if l1 < l2 /\ forall ( r in resources)(resource_provisions[l1,r] = resource_provisions[l2,r] )
|
||||
then
|
||||
if costs[l1] > costs[l2]
|
||||
then lex_greatereq(
|
||||
[comp_locations[l2,c] | c in comps],
|
||||
[comp_locations[l1,c] | c in comps])
|
||||
/\
|
||||
(used_locations[l1] = 1 -> used_locations[l2] = 1)
|
||||
else
|
||||
lex_greatereq(
|
||||
[comp_locations[l1,c] | c in comps],
|
||||
[comp_locations[l2,c] | c in comps])
|
||||
/\
|
||||
(used_locations[l2] = 1 -> used_locations[l1] = 1)
|
||||
endif
|
||||
else
|
||||
true
|
||||
endif
|
||||
));
|
||||
|
||||
|
||||
%------------------------------------------------------------------------------%
|
||||
% Redundant constraints
|
||||
|
||||
%constraint redundant_constraint(
|
||||
% % Ralf constraints
|
||||
% forall (rcomp in comps, port in ports)(
|
||||
% if requirement_port_nums[rcomp,port]!=0
|
||||
% then
|
||||
% comps_num[rcomp] > 0 -> sum( mport in multi_provide_ports, pcomp in comps)(
|
||||
% if provide_port_nums[pcomp,mport] != 0 /\ multi_provides[mport,port]
|
||||
% then comps_num[pcomp]
|
||||
% else 0
|
||||
% endif ) >= requirement_port_nums[rcomp,port]
|
||||
% else
|
||||
% true
|
||||
% endif
|
||||
% ));
|
||||
|
||||
%------------------------------------------------------------------------------%
|
||||
% Constraints
|
||||
constraint
|
||||
( sum(l in locations)(comp_locations[l,1]) > 0
|
||||
\/ sum(l in locations)(comp_locations[l,2]) > 0
|
||||
)
|
||||
/\ forall(x in locations)(comp_locations[x,3] < 2)
|
||||
/\ forall(x in locations)(comp_locations[x,4] < 2)
|
||||
;
|
||||
|
||||
int: obj_min = sum(l in locations)(if costs[l] < 0 then costs[l] else 0 endif);
|
||||
int: obj_max = sum(l in locations)(if costs[l] > 0 then costs[l] else 0 endif);
|
||||
var obj_min..obj_max: objective;
|
||||
|
||||
constraint objective = sum(l in locations)(used_locations[l] * costs[l]);
|
||||
|
||||
%------------------------------------------------------------------------------%
|
||||
% Solve item
|
||||
|
||||
array [locations] of locations: costs_asc = arg_sort(costs);
|
||||
array [locations] of locations: costs_desc = reverse(costs_asc);
|
||||
|
||||
solve
|
||||
:: seq_search([
|
||||
int_search([used_locations[costs_desc[i]] | i in locations],
|
||||
input_order, indomain_min, complete),
|
||||
int_search([comp_locations[l, i] | l in locations, i in comps],
|
||||
first_fail, indomain_max, complete),
|
||||
int_search(comps_num, first_fail, indomain_max, complete),
|
||||
int_search([bindings[m,p,i,j] | m in multi_provide_ports, p in ports, i,j in comps],
|
||||
first_fail, indomain_max, complete)
|
||||
])
|
||||
minimize objective;
|
||||
|
||||
%------------------------------------------------------------------------------%
|
||||
% Output item
|
||||
|
||||
output [
|
||||
"bindings = array4d(\(multi_provide_ports), \(ports), \(comps), \(comps), \(bindings));\n",
|
||||
"comps_num = \(comps_num);\n",
|
||||
"comp_locations = array2d(\(locations), \(comps), \(comp_locations));\n",
|
||||
"used_locations = \(used_locations);\n",
|
||||
"objective = \(objective);\n",
|
||||
"% [\(objective), \(sum(x in locations)(sum(y in comps)(comp_locations[x,y])))]\n"
|
||||
];
|
||||
|
||||
|
||||
Reference in New Issue
Block a user