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Kilokem
2024-10-29 19:15:26 +01:00
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BIN
gyakorlatok/Feladatok_v1.docx Normal file
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gyakorlatok/csarnok.mod Normal file
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var a >= 0, integer;
var b >= 0, integer;
s.t. lemez: a*4000 + b*5000 <= 32000;
s.t. acel: a*3 + b*3 <= 24;
s.t. tetofedo: a*300 + b*200 <= 2000;
s.t. beton: a*200 + b*100 <= 1600;
maximize nyereseg: a*4000 + b*5000;
end;

31
gyakorlatok/csarnok.out Normal file
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Problem: csarnok
Rows: 5
Columns: 2 (2 integer, 0 binary)
Non-zeros: 10
Status: INTEGER OPTIMAL
Objective: nyereseg = 32000 (MAXimum)
No. Row name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 lemez 32000 32000
2 acel 21 24
3 tetofedo 1700 2000
4 beton 1000 1600
5 nyereseg 32000
No. Column name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 a * 3 0
2 b * 4 0
Integer feasibility conditions:
KKT.PE: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
KKT.PB: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
End of output

9
gyakorlatok/cvitamin.mod Normal file
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var alma >= 0, integer;
var citrom >= 0, integer;
s.t. kaloria: alma*80 + citrom*50 <= 400;
s.t. vitamin: alma*100 + citrom*300 >= 500;
s.t. vas: alma*0.5 + citrom*0.2 >= 1.2;
minimize gyumolcs: alma*40 + citrom*60;
end;

30
gyakorlatok/cvitamin.out Normal file
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Problem: cvitamin
Rows: 4
Columns: 2 (2 integer, 0 binary)
Non-zeros: 8
Status: INTEGER OPTIMAL
Objective: gyumolcs = 140 (MINimum)
No. Row name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 kaloria 210 400
2 vitamin 500 500
3 vas 1.2 1.2
4 gyumolcs 140
No. Column name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 alma * 2 0
2 citrom * 1 0
Integer feasibility conditions:
KKT.PE: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
KKT.PB: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
End of output

17
gyakorlatok/fesztival.mod Normal file
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#Fesztival
var F1 binary;
var F2 binary;
var F3 binary;
var F4 binary;
var F5 binary;
s.t. Haggard: F1 + F3 + F4 >= 1;
s.t. Stratovarius: F1 + F2 + F3 + F5>= 1;
s.t. Epica: F1 + F2 + F4 + F5 >= 1;
s.t. Dalriada: F3 + F5 >= 1;
s.t. Apocalyptica: F4 >= 1;
s.t. Liva: F2 + F3 + F4 + F5 >= 1;
s.t. Eluveitie: F3 + F5 >= 1;
minimize NumberOfFestivals: F1 + F2 + F3 + F4 + F5;

38
gyakorlatok/fesztival.out Normal file
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Problem: fesztival
Rows: 8
Columns: 5 (5 integer, 5 binary)
Non-zeros: 25
Status: INTEGER OPTIMAL
Objective: NumberOfFestivals = 2 (MINimum)
No. Row name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 Haggard 2 1
2 Stratovarius 1 1
3 Epica 1 1
4 Dalriada 1 1
5 Apocalyptica 1 1
6 Liva 2 1
7 Eluveitie 1 1
8 NumberOfFestivals
2
No. Column name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 F1 * 0 0 1
2 F2 * 0 0 1
3 F3 * 1 0 1
4 F4 * 1 0 1
5 F5 * 0 0 1
Integer feasibility conditions:
KKT.PE: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
KKT.PB: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
End of output

62
gyakorlatok/forgatas.mod Normal file
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set Actors;
param salary {Actors} >=0;
param sceneCount;
set Scene:=1..sceneCount;
param time{Scene} >=0;
param shooting {Scene, Actors} binary;
param dayCount;
set Days:=1..dayCount;
param hoursADay;
var doScene{Scene, Days} binary;
var actorComeIn{Actors, Days} binary;
#Max forgat<EFBFBD>si id<EFBFBD>
s.t. MaxShootingHoursADay{d in Days}: sum{s in Scene} doScene[s, d] * time[s] <= hoursADay;
#Forgat e a sz<EFBFBD>n<EFBFBD>sz
s.t. IfActorActsADay{d in Days, s in Scene, a in Actors: shooting[s,a]==1}: doScene [s, d] <= actorComeIn[a, d];
#Minden jelenet legyen leforgatva
s.t. DoAllScene {s in Scene}: sum{d in Days} doScene[s, d]=1;
minimize CostOfShooting: sum{ d in Days, a in Actors} actorComeIn[a, d] * salary [a];
data;
set Actors:= A B C D E;
param sceneCount:=5;
param dayCount:=10;
param hoursADay:=8;
param salary:=
A 180
B 280
C 250
D 230
E 450
;
param shooting:
A B C D E :=
1 1 0 0 0 1
2 0 1 1 1 0
3 1 0 0 1 1
4 0 1 1 0 0
5 0 0 1 1 0
;
param time:=
1 1
2 1.5
3 2.3
4 1.4
5 1.7
;

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gyakorlatok/forgatas.out Normal file
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Problem: forgatas
Rows: 136
Columns: 100 (100 integer, 100 binary)
Non-zeros: 390
Status: INTEGER OPTIMAL
Objective: CostOfShooting = 1390 (MINimum)
No. Row name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 MaxShootingHoursADay[1]
0 8
2 MaxShootingHoursADay[2]
0 8
3 MaxShootingHoursADay[3]
0 8
4 MaxShootingHoursADay[4]
0 8
5 MaxShootingHoursADay[5]
0 8
6 MaxShootingHoursADay[6]
0 8
7 MaxShootingHoursADay[7]
0 8
8 MaxShootingHoursADay[8]
0 8
9 MaxShootingHoursADay[9]
0 8
10 MaxShootingHoursADay[10]
7.9 8
11 IfActorActsADay[1,1,A]
0 -0
12 IfActorActsADay[1,1,E]
0 -0
13 IfActorActsADay[1,2,B]
0 -0
14 IfActorActsADay[1,2,C]
0 -0
15 IfActorActsADay[1,2,D]
0 -0
16 IfActorActsADay[1,3,A]
0 -0
17 IfActorActsADay[1,3,D]
0 -0
18 IfActorActsADay[1,3,E]
0 -0
19 IfActorActsADay[1,4,B]
0 -0
20 IfActorActsADay[1,4,C]
0 -0
21 IfActorActsADay[1,5,C]
0 -0
22 IfActorActsADay[1,5,D]
0 -0
23 IfActorActsADay[2,1,A]
0 -0
24 IfActorActsADay[2,1,E]
0 -0
25 IfActorActsADay[2,2,B]
0 -0
26 IfActorActsADay[2,2,C]
0 -0
27 IfActorActsADay[2,2,D]
0 -0
28 IfActorActsADay[2,3,A]
0 -0
29 IfActorActsADay[2,3,D]
0 -0
30 IfActorActsADay[2,3,E]
0 -0
31 IfActorActsADay[2,4,B]
0 -0
32 IfActorActsADay[2,4,C]
0 -0
33 IfActorActsADay[2,5,C]
0 -0
34 IfActorActsADay[2,5,D]
0 -0
35 IfActorActsADay[3,1,A]
0 -0
36 IfActorActsADay[3,1,E]
0 -0
37 IfActorActsADay[3,2,B]
0 -0
38 IfActorActsADay[3,2,C]
0 -0
39 IfActorActsADay[3,2,D]
0 -0
40 IfActorActsADay[3,3,A]
0 -0
41 IfActorActsADay[3,3,D]
0 -0
42 IfActorActsADay[3,3,E]
0 -0
43 IfActorActsADay[3,4,B]
0 -0
44 IfActorActsADay[3,4,C]
0 -0
45 IfActorActsADay[3,5,C]
0 -0
46 IfActorActsADay[3,5,D]
0 -0
47 IfActorActsADay[4,1,A]
0 -0
48 IfActorActsADay[4,1,E]
0 -0
49 IfActorActsADay[4,2,B]
0 -0
50 IfActorActsADay[4,2,C]
0 -0
51 IfActorActsADay[4,2,D]
0 -0
52 IfActorActsADay[4,3,A]
0 -0
53 IfActorActsADay[4,3,D]
0 -0
54 IfActorActsADay[4,3,E]
0 -0
55 IfActorActsADay[4,4,B]
0 -0
56 IfActorActsADay[4,4,C]
0 -0
57 IfActorActsADay[4,5,C]
0 -0
58 IfActorActsADay[4,5,D]
0 -0
59 IfActorActsADay[5,1,A]
0 -0
60 IfActorActsADay[5,1,E]
0 -0
61 IfActorActsADay[5,2,B]
0 -0
62 IfActorActsADay[5,2,C]
0 -0
63 IfActorActsADay[5,2,D]
0 -0
64 IfActorActsADay[5,3,A]
0 -0
65 IfActorActsADay[5,3,D]
0 -0
66 IfActorActsADay[5,3,E]
0 -0
67 IfActorActsADay[5,4,B]
0 -0
68 IfActorActsADay[5,4,C]
0 -0
69 IfActorActsADay[5,5,C]
0 -0
70 IfActorActsADay[5,5,D]
0 -0
71 IfActorActsADay[6,1,A]
0 -0
72 IfActorActsADay[6,1,E]
0 -0
73 IfActorActsADay[6,2,B]
0 -0
74 IfActorActsADay[6,2,C]
0 -0
75 IfActorActsADay[6,2,D]
0 -0
76 IfActorActsADay[6,3,A]
0 -0
77 IfActorActsADay[6,3,D]
0 -0
78 IfActorActsADay[6,3,E]
0 -0
79 IfActorActsADay[6,4,B]
0 -0
80 IfActorActsADay[6,4,C]
0 -0
81 IfActorActsADay[6,5,C]
0 -0
82 IfActorActsADay[6,5,D]
0 -0
83 IfActorActsADay[7,1,A]
0 -0
84 IfActorActsADay[7,1,E]
0 -0
85 IfActorActsADay[7,2,B]
0 -0
86 IfActorActsADay[7,2,C]
0 -0
87 IfActorActsADay[7,2,D]
0 -0
88 IfActorActsADay[7,3,A]
0 -0
89 IfActorActsADay[7,3,D]
0 -0
90 IfActorActsADay[7,3,E]
0 -0
91 IfActorActsADay[7,4,B]
0 -0
92 IfActorActsADay[7,4,C]
0 -0
93 IfActorActsADay[7,5,C]
0 -0
94 IfActorActsADay[7,5,D]
0 -0
95 IfActorActsADay[8,1,A]
0 -0
96 IfActorActsADay[8,1,E]
0 -0
97 IfActorActsADay[8,2,B]
0 -0
98 IfActorActsADay[8,2,C]
0 -0
99 IfActorActsADay[8,2,D]
0 -0
100 IfActorActsADay[8,3,A]
0 -0
101 IfActorActsADay[8,3,D]
0 -0
102 IfActorActsADay[8,3,E]
0 -0
103 IfActorActsADay[8,4,B]
0 -0
104 IfActorActsADay[8,4,C]
0 -0
105 IfActorActsADay[8,5,C]
0 -0
106 IfActorActsADay[8,5,D]
0 -0
107 IfActorActsADay[9,1,A]
0 -0
108 IfActorActsADay[9,1,E]
0 -0
109 IfActorActsADay[9,2,B]
0 -0
110 IfActorActsADay[9,2,C]
0 -0
111 IfActorActsADay[9,2,D]
0 -0
112 IfActorActsADay[9,3,A]
0 -0
113 IfActorActsADay[9,3,D]
0 -0
114 IfActorActsADay[9,3,E]
0 -0
115 IfActorActsADay[9,4,B]
0 -0
116 IfActorActsADay[9,4,C]
0 -0
117 IfActorActsADay[9,5,C]
0 -0
118 IfActorActsADay[9,5,D]
0 -0
119 IfActorActsADay[10,1,A]
0 -0
120 IfActorActsADay[10,1,E]
0 -0
121 IfActorActsADay[10,2,B]
0 -0
122 IfActorActsADay[10,2,C]
0 -0
123 IfActorActsADay[10,2,D]
0 -0
124 IfActorActsADay[10,3,A]
0 -0
125 IfActorActsADay[10,3,D]
0 -0
126 IfActorActsADay[10,3,E]
0 -0
127 IfActorActsADay[10,4,B]
0 -0
128 IfActorActsADay[10,4,C]
0 -0
129 IfActorActsADay[10,5,C]
0 -0
130 IfActorActsADay[10,5,D]
0 -0
131 DoAllScene[1]
1 1 =
132 DoAllScene[2]
1 1 =
133 DoAllScene[3]
1 1 =
134 DoAllScene[4]
1 1 =
135 DoAllScene[5]
1 1 =
136 CostOfShooting
1390
No. Column name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 doScene[1,1] * 0 0 1
2 doScene[2,1] * 0 0 1
3 doScene[3,1] * 0 0 1
4 doScene[4,1] * 0 0 1
5 doScene[5,1] * 0 0 1
6 doScene[1,2] * 0 0 1
7 doScene[2,2] * 0 0 1
8 doScene[3,2] * 0 0 1
9 doScene[4,2] * 0 0 1
10 doScene[5,2] * 0 0 1
11 doScene[1,3] * 0 0 1
12 doScene[2,3] * 0 0 1
13 doScene[3,3] * 0 0 1
14 doScene[4,3] * 0 0 1
15 doScene[5,3] * 0 0 1
16 doScene[1,4] * 0 0 1
17 doScene[2,4] * 0 0 1
18 doScene[3,4] * 0 0 1
19 doScene[4,4] * 0 0 1
20 doScene[5,4] * 0 0 1
21 doScene[1,5] * 0 0 1
22 doScene[2,5] * 0 0 1
23 doScene[3,5] * 0 0 1
24 doScene[4,5] * 0 0 1
25 doScene[5,5] * 0 0 1
26 doScene[1,6] * 0 0 1
27 doScene[2,6] * 0 0 1
28 doScene[3,6] * 0 0 1
29 doScene[4,6] * 0 0 1
30 doScene[5,6] * 0 0 1
31 doScene[1,7] * 0 0 1
32 doScene[2,7] * 0 0 1
33 doScene[3,7] * 0 0 1
34 doScene[4,7] * 0 0 1
35 doScene[5,7] * 0 0 1
36 doScene[1,8] * 0 0 1
37 doScene[2,8] * 0 0 1
38 doScene[3,8] * 0 0 1
39 doScene[4,8] * 0 0 1
40 doScene[5,8] * 0 0 1
41 doScene[1,9] * 0 0 1
42 doScene[2,9] * 0 0 1
43 doScene[3,9] * 0 0 1
44 doScene[4,9] * 0 0 1
45 doScene[5,9] * 0 0 1
46 doScene[1,10]
* 1 0 1
47 doScene[2,10]
* 1 0 1
48 doScene[3,10]
* 1 0 1
49 doScene[4,10]
* 1 0 1
50 doScene[5,10]
* 1 0 1
51 actorComeIn[A,1]
* 0 0 1
52 actorComeIn[E,1]
* 0 0 1
53 actorComeIn[B,1]
* 0 0 1
54 actorComeIn[C,1]
* 0 0 1
55 actorComeIn[D,1]
* 0 0 1
56 actorComeIn[A,2]
* 0 0 1
57 actorComeIn[E,2]
* 0 0 1
58 actorComeIn[B,2]
* 0 0 1
59 actorComeIn[C,2]
* 0 0 1
60 actorComeIn[D,2]
* 0 0 1
61 actorComeIn[A,3]
* 0 0 1
62 actorComeIn[E,3]
* 0 0 1
63 actorComeIn[B,3]
* 0 0 1
64 actorComeIn[C,3]
* 0 0 1
65 actorComeIn[D,3]
* 0 0 1
66 actorComeIn[A,4]
* 0 0 1
67 actorComeIn[E,4]
* 0 0 1
68 actorComeIn[B,4]
* 0 0 1
69 actorComeIn[C,4]
* 0 0 1
70 actorComeIn[D,4]
* 0 0 1
71 actorComeIn[A,5]
* 0 0 1
72 actorComeIn[E,5]
* 0 0 1
73 actorComeIn[B,5]
* 0 0 1
74 actorComeIn[C,5]
* 0 0 1
75 actorComeIn[D,5]
* 0 0 1
76 actorComeIn[A,6]
* 0 0 1
77 actorComeIn[E,6]
* 0 0 1
78 actorComeIn[B,6]
* 0 0 1
79 actorComeIn[C,6]
* 0 0 1
80 actorComeIn[D,6]
* 0 0 1
81 actorComeIn[A,7]
* 0 0 1
82 actorComeIn[E,7]
* 0 0 1
83 actorComeIn[B,7]
* 0 0 1
84 actorComeIn[C,7]
* 0 0 1
85 actorComeIn[D,7]
* 0 0 1
86 actorComeIn[A,8]
* 0 0 1
87 actorComeIn[E,8]
* 0 0 1
88 actorComeIn[B,8]
* 0 0 1
89 actorComeIn[C,8]
* 0 0 1
90 actorComeIn[D,8]
* 0 0 1
91 actorComeIn[A,9]
* 0 0 1
92 actorComeIn[E,9]
* 0 0 1
93 actorComeIn[B,9]
* 0 0 1
94 actorComeIn[C,9]
* 0 0 1
95 actorComeIn[D,9]
* 0 0 1
96 actorComeIn[A,10]
* 1 0 1
97 actorComeIn[E,10]
* 1 0 1
98 actorComeIn[B,10]
* 1 0 1
99 actorComeIn[C,10]
* 1 0 1
100 actorComeIn[D,10]
* 1 0 1
Integer feasibility conditions:
KKT.PE: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
KKT.PB: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
End of output

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gyakorlatok/froccs.mod Normal file
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var kf >=0, integer;
var nf >=0, integer;
var hl >=0, integer;
var hm >=0, integer;
var vh >=0, integer;
var krf >=0, integer;
var sf >=0, integer;
var pf >=0, integer;
var hu >=0, integer;
var lf >=0, integer;
var pm >=0, integer;
var maf >=0, integer;
var csat >=0, integer;
var lmp >=0, integer;
var kaszf >=0, integer;
var harm >=0, integer;
s.t. bor: kf*1 + nf*2 + hl*1 + hm*3 + vh*2 +krf*9 + sf*1 + pf*6 + hu*4 + lf*1 + pm*6 + maf*0.5 + csat*1 + lmp*1.5 + kaszf*7 +harm*1 <= 100;
s.t. szoda: kf*1 + nf*1 + hl*2 + hm*2 + vh*3 +krf*1 + sf*9 + pf*3 + hu*1 + lf*4 + pm*4 + maf*0.5 + csat*0.5 + lmp*0.5 + kaszf*3 +harm*5 <= 150;
maximize arbevetel: (kf*200 + nf*330 + hl*210 + hm*470 + vh*400 + krf*1500 + sf*300 + pf*900 + hu*600 +lf*250 + pm*1000 + maf*150 + csat*170 + lmp*300 + kaszf*1100 +harm*300)*10;
end;

37
gyakorlatok/froccs.out Normal file
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Problem: froccs
Rows: 3
Columns: 10 (10 integer, 0 binary)
Non-zeros: 30
Status: INTEGER OPTIMAL
Objective: arbevetel = 208200 (MAXimum)
No. Row name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 bor 100 100
2 szoda 150 150
3 arbevetel 208200
No. Column name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 kf * 82 0
2 nf * 0 0
3 hl * 2 0
4 hm * 0 0
5 vh * 0 0
6 krf * 0 0
7 sf * 0 0
8 pf * 0 0
9 hu * 0 0
10 lf * 16 0
Integer feasibility conditions:
KKT.PE: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
KKT.PB: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
End of output

23
gyakorlatok/froccs_kie Normal file
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var kf >=0, integer;
var nf >=0, integer;
var hl >=0, integer;
var hm >=0, integer;
var vh >=0, integer;
var krf >=0, integer;
var sf >=0, integer;
var pf >=0, integer;
var hu >=0, integer;
var lf >=0, integer;
var pm >=0, integer;
var maf >=0, integer;
var csat >=0, integer;
var lmp >=0, integer;
var kaszf >=0, integer;
var harm >=0, integer;
s.t. bor: kf*1 + nf*2 + hl*1 + hm*3 + vh*2 +krf*9 + sf*1 + pf*6 + hu*4 + lf*1 + pm*6 + maf*0.5 + csat*1 + lmp*1.5 + kaszf*7 +harm*1 <= 100;
s.t. szoda: kf*1 + nf*1 + hl*2 + hm*2 + vh*3 +krf*1 + sf*9 + pf*3 + hu*1 + lf*4 + pm*4 + maf*0.5 + csat*0.5 + lmp*0.5 + kaszf*3 +harm*5 <= 150;
maximize arbevetel: (kf*200 + nf*330 + hl*210 + hm*470 + vh*400 + krf*1500 + sf*300 + pf*900 + hu*600 +lf*250 + pm*1000 + maf*150 + csat*170 + lmp*300 + kaszf*1100 +harm*300)*10;
end;

46
gyakorlatok/froccs_kieg.mod Normal file
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var kf >=0, integer;
var nf >=0, integer;
var hl >=0, integer;
var hm >=0, integer;
var vh >=0, integer;
var krf >=0, integer;
var sf >=0, integer;
var pf >=0, integer;
var hu >=0, integer;
var lf >=0, integer;
var pm >=0, integer;
var maf >=0, integer;
var csat >=0, integer;
var lmp >=0, integer;
var kaszf >=0, integer;
var harm >=0, integer;
#extra
#Maci fr<EFBFBD>ccs: 1 feh<EFBFBD>rbor, 1.9 sz<EFBFBD>da, 0.1 msz<EFBFBD>rp - 800 ft
#Szerencs<EFBFBD>sfl<EFBFBD>t<EFBFBD>s: 1 fbor, 1 rum, 1 sz<EFBFBD>da - 900 ft
#<EFBFBD>jh<EFBFBD>zi fr<EFBFBD>ccs: 1 fbor <EFBFBD>s 2 kuborka - 150 ft
#Nagy medve: 3 vbor, 1 rum, 1 k<EFBFBD>la - 1200 ft
#kisvad<EFBFBD>sz: 1 vbor, 1 k<EFBFBD>la - 500 ft
#nagyvad<EFBFBD>sz: 2 vbor, 1 k<EFBFBD>la - 650 ft
var maci >= 0, integer;
var szerencs >= 0, integer;
var uf >= 0, integer;
var nagym >= 0, integer;
var kisv >= 0, integer;
var nagyv >= 0, integer;
#M<EFBFBD>lnasz<EFBFBD>rp: 10l, Rum 20 l, Uborka 10 l, k<EFBFBD>la 20 l, vbor 50l
s.t. bor: kf*1 + nf*2 + hl*1 + hm*3 + vh*2 +krf*9 + sf*1 + pf*6 + hu*4 + lf*1 + pm*6 + maf*0.5 + csat*1 + lmp*1.5 + kaszf*7 +harm*1 + maci*1 + szerencs*1 + uf*1 <= 1000;
s.t. szoda: kf*1 + nf*1 + hl*2 + hm*2 + vh*3 +krf*1 + sf*9 + pf*3 + hu*1 + lf*4 + pm*4 + maf*0.5 + csat*0.5 + lmp*0.5 + kaszf*3 +harm*5 + maci*1.9 + szerencs*1 <= 1500;
s.t. rum: szerencs*1 +nagym*1 <= 200;
s.t. szorp: maci*0.1 <= 100;
s.t. uborka: uf*2 <= 100;
s.t. kola: nagym*1 + kisv*1 + nagyv*1 <= 200;
s.t. vbor: nagym*3 + kisv*1 + nagyv*2 <= 500;
maximize arbevetel: (kf*200 + nf*330 + hl*210 + hm*470 + vh*400 + krf*1500 + sf*300 + pf*900 + hu*600 +lf*250 + pm*1000 + maf*150 + csat*170 + lmp*300 + kaszf*1100 +harm*300 + maci*800 + szerencs*900 + uf*150 + nagym*1200 + kisv*500 + nagyv*650);
end;

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Problem: froccs_kieg
Rows: 8
Columns: 22 (22 integer, 0 binary)
Non-zeros: 69
Status: INTEGER OPTIMAL
Objective: arbevetel = 886250 (MAXimum)
No. Row name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 bor 1000 1000
2 szoda 1500 1500
3 rum 200 200
4 szorp 73 100
5 uborka 90 100
6 kola 200 200
7 vbor 500 500
8 arbevetel 886250
No. Column name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 kf * 0 0
2 nf * 0 0
3 hl * 0 0
4 hm * 0 0
5 vh * 0 0
6 krf * 14 0
7 sf * 0 0
8 pf * 0 0
9 hu * 0 0
10 lf * 0 0
11 pm * 0 0
12 maf * 0 0
13 csat * 0 0
14 lmp * 0 0
15 kaszf * 0 0
16 harm * 0 0
17 maci * 730 0
18 szerencs * 99 0
19 uf * 45 0
20 nagym * 101 0
21 kisv * 1 0
22 nagyv * 98 0
Integer feasibility conditions:
KKT.PE: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
KKT.PB: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
End of output

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set Froccs;
set Ingredients;
var kf >=0, integer;
var nf >=0, integer;
var hl >=0, integer;
var hm >=0, integer;
var vh >=0, integer;
var krf >=0, integer;
var sf >=0, integer;
var pf >=0, integer;
var hu >=0, integer;
var lf >=0, integer;
s.t. bor: kf*1 + nf*2 + hl*1 + hm*3 + vh*2 +krf*9 + sf*1 + pf*6 + hu*4 + lf*1 <= 1000;
s.t. szoda: kf*1 + nf*1 + hl*2 + hm*2 + vh*3 +krf*1 + sf*9 + pf*3 + hu*1 + lf*4 <= 1500;
maximize arbevetel: (kf*200 + nf*330 + hl*210 + hm*470 + vh*400 + krf*1500 + sf*300 + pf*900 + hu*600 +lf*250 );
end;

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set Froccs;
set Ingredients;
var Sale {Froccs} >= 0, integer;
param HowMany {Froccs, Ingredients};
param Price {Froccs};
param Use {Ingredients};
s.t. UseIngredietns{i in Ingredients}:sum{f in Froccs}HowMany[f,i]*Sale[f] <= Use[i];
maximize TotalIncome: sum{f in Froccs} Sale[f]*Price[f];
data;
set Froccs:= kf, nf, hl, hm, vh, krf, sf, pf, hu, lf;
set Ingredients:= Wine, Soda;
param HowMany:
Wine Soda:=
kf 1 1
nf 2 1
hl 1 2
hm 3 2
vh 2 3
krf 9 1
sf 1 9
pf 6 3
hu 4 1
lf 1 4
;
param Price:=
kf 200
nf 330
hl 210
hm 470
vh 400
krf 1500
sf 300
pf 900
hu 600
lf 250
;
param Use:=
Wine 1000
Soda 1500
;
end;

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Problem: froccs_kieg_2
Rows: 3
Columns: 10 (10 integer, 0 binary)
Non-zeros: 30
Status: INTEGER OPTIMAL
Objective: TotalIncome = 208320 (MAXimum)
No. Row name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 UseIngredietns[Wine]
1000 1000
2 UseIngredietns[Soda]
1500 1500
3 TotalIncome 208320
No. Column name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 Sale[kf] * 832 0
2 Sale[nf] * 0 0
3 Sale[hl] * 2 0
4 Sale[hm] * 0 0
5 Sale[vh] * 0 0
6 Sale[krf] * 0 0
7 Sale[sf] * 0 0
8 Sale[pf] * 0 0
9 Sale[hu] * 0 0
10 Sale[lf] * 166 0
Integer feasibility conditions:
KKT.PE: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
KKT.PB: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
End of output

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var T1 >= 0, integer;
var T2 >= 0, integer;
s.t. G1: 3*T1 + 4*T2 <=130;
s.t. G2: 4*T1 + 6*T2 <=130;
s.t. szerelde: 1*T1 + 2*T2 <= 60;
maximize arbevetel: 8*T1 + 10*T2;
end;

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Problem: gyartas
Rows: 4
Columns: 2 (2 integer, 0 binary)
Non-zeros: 8
Status: INTEGER OPTIMAL
Objective: arbevetel = 258 (MAXimum)
No. Row name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 G1 97 130
2 G2 130 130
3 szerelde 33 60
4 arbevetel 258
No. Column name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 T1 * 31 0
2 T2 * 1 0
Integer feasibility conditions:
KKT.PE: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
KKT.PB: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
End of output

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#Happy feladat
#Webes projekt csapat, 3-4 f<EFBFBD>, minden jobban kell mag<EFBFBD>t <EFBFBD>reznie a csapattagoknak <EFBFBD>s a skilleknek is meg kell lennie
# |Frontend|Backend |Database| CSS |Agility |DevOps |
#Tibor | | X | | X | | |
#D<EFBFBD>vid | X | | | X | | |
#Botond | | | X | | X | |
#Bence | | X | X | X | | X |
#M<EFBFBD>rk | X | | | | X | |
#Bal<EFBFBD>zs | | | X | | | X |
#Kedvelts<EFBFBD>g: Tibor 0, D<EFBFBD>vid 8, Botond -2, Bence 4, M<EFBFBD>rk 3, Bal<EFBFBD>zs -10
var t binary;
var d binary;
var bo binary;
var be binary;
var m binary;
var b binary;
s.t. front: d+m >= 1;
s.t. back: t+be >= 1;
s.t. datab: bo+be+b >= 1;
s.t. css: t+d+be >= 1;
s.t. agi: bo+m >= 1;
s.t. dev: be+b >= 1;
s.t. letszam: 3 <= t + d + bo + be + m + b <= 4;
maximize skill: t*0+d*8+bo*(-2)+be*4+m*3+b*(-10);

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Problem: happy
Rows: 8
Columns: 6 (6 integer, 6 binary)
Non-zeros: 25
Status: INTEGER OPTIMAL
Objective: skill = 15 (MAXimum)
No. Row name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 front 2 1
2 back 2 1
3 datab 1 1
4 css 3 1
5 agi 1 1
6 dev 1 1
7 letszam 4 3 4
8 skill 15
No. Column name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 t * 1 0 1
2 d * 1 0 1
3 bo * 0 0 1
4 be * 1 0 1
5 m * 1 0 1
6 b * 0 0 1
Integer feasibility conditions:
KKT.PE: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
KKT.PB: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
End of output

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var tura >=0, integer;
var mini >=0, integer;
s.t. munkaido: 45 * tura + 40 * mini <= 35*(40*60);
s.t. maxt: tura <= 100;
s.t. maxm: mini <= 1200;
s.t. anyag: tura * 3 + 2 * mini <= 5400;
maximize haszon: tura * 32 + mini * 24;
end;

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Problem: hatizsak
Rows: 5
Columns: 2 (2 integer, 0 binary)
Non-zeros: 8
Status: INTEGER OPTIMAL
Objective: haszon = 32000 (MAXimum)
No. Row name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 munkaido 52500 84000
2 maxt 100 100
3 maxm 1200 1200
4 anyag 2700 5400
5 haszon 32000
No. Column name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 tura * 100 0
2 mini * 1200 0
Integer feasibility conditions:
KKT.PE: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
KKT.PB: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
End of output

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var lekvar >= 0, integer;
var befott >= 0, integer;
s.t. cukor: lekvar*40 + befott*40 <= 8000;
s.t. gyum: lekvar*80 + befott*40 <= 12000;
maximize profit: lekvar*120 + befott*80;
end;

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Problem: lekvar
Rows: 3
Columns: 2 (2 integer, 0 binary)
Non-zeros: 6
Status: INTEGER OPTIMAL
Objective: profit = 20000 (MAXimum)
No. Row name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 cukor 8000 8000
2 gyum 12000 12000
3 profit 20000
No. Column name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 lekvar * 100 0
2 befott * 100 0
Integer feasibility conditions:
KKT.PE: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
KKT.PB: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
End of output

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# Halmazok <EFBFBD>s param<EFBFBD>terek
set Mezo; # Mez<EFBFBD>
set Malom; # Malom
set Pekseg; # P<EFBFBD>ks<EFBFBD>gek
param Buza {Mezo} >= 0; # Mez<EFBFBD>n termelt b<EFBFBD>za
param MalomKapacitas {Malom} >= 0; # Malmok kapacit<EFBFBD>sa
param TavolsagMezoMalom {Mezo, Malom} >= 0; # Mez<EFBFBD> <EFBFBD>s malom k<EFBFBD>z<EFBFBD>tti t<EFBFBD>vols<EFBFBD>g
param TavolsagMalomPekseg {Malom, Pekseg} >= 0; # Malom <EFBFBD>s p<EFBFBD>ks<EFBFBD>g k<EFBFBD>z<EFBFBD>tti t<EFBFBD>vols<EFBFBD>g
param TeherautoKapacitas; # Teheraut<EFBFBD> kapacit<EFBFBD>sa (kg)
param OrlesArany; # <EFBFBD>rl<EFBFBD>si ar<EFBFBD>ny (liszt/b<EFBFBD>za)
param UresFogyasztas; # <EFBFBD>res teheraut<EFBFBD> fogyaszt<EFBFBD>s (l/100 km)
param ValtozoFogyasztas; # V<EFBFBD>ltoz<EFBFBD> fogyaszt<EFBFBD>s (l/kg/100 km)
param Benzinar; # Benzin <EFBFBD>ra (Ft/100 km)
# V<EFBFBD>ltoz<EFBFBD>k
var SzallitasMezoMalom {Mezo, Malom} >= 0; # Sz<EFBFBD>ll<EFBFBD>tott b<EFBFBD>za mennyis<EFBFBD>ge mez<EFBFBD>r<EFBFBD>l malomba
var SzallitasMalomPekseg {Malom, Pekseg} >= 0; # Sz<EFBFBD>ll<EFBFBD>tott liszt mennyis<EFBFBD>ge malomb<EFBFBD>l p<EFBFBD>ks<EFBFBD>gbe
# Korl<EFBFBD>toz<EFBFBD>sok
# Minden mez<EFBFBD>r<EFBFBD>l csak a termelt mennyis<EFBFBD>g sz<EFBFBD>ll<EFBFBD>that<EFBFBD>
s.t. KeszletKorlatozas {m in Mezo}:
sum {l in Malom} SzallitasMezoMalom[m, l] <= Buza[m];
# Malom kapacit<EFBFBD>s<EFBFBD>nak figyelembev<EFBFBD>tele
s.t. MalomKapacitasKorlatozas {l in Malom}:
sum {m in Mezo} SzallitasMezoMalom[m, l] <= MalomKapacitas[l];
# <EFBFBD>rl<EFBFBD>si ar<EFBFBD>ny figyelembev<EFBFBD>tele (malomb<EFBFBD>l csak a megfelel<EFBFBD> lisztmennyis<EFBFBD>get lehet sz<EFBFBD>ll<EFBFBD>tani)
s.t. OrlesiAranyKorlatozas {l in Malom}:
sum {p in Pekseg} SzallitasMalomPekseg[l, p] <= sum {m in Mezo} SzallitasMezoMalom[m, l] * OrlesArany;
# K<EFBFBD>lts<EFBFBD>gf<EFBFBD>ggv<EFBFBD>ny
minimize TeljesUzemanyagKoltseg:
# Mez<EFBFBD>r<EFBFBD>l malmokba sz<EFBFBD>ll<EFBFBD>t<EFBFBD>s
sum {m in Mezo, l in Malom}
(UresFogyasztas + ValtozoFogyasztas * SzallitasMezoMalom[m, l]) * TavolsagMezoMalom[m, l] * Benzinar
+
# Malmokb<EFBFBD>l p<EFBFBD>ks<EFBFBD>gekbe sz<EFBFBD>ll<EFBFBD>t<EFBFBD>s
sum {l in Malom, p in Pekseg}
(UresFogyasztas + ValtozoFogyasztas * SzallitasMalomPekseg[l, p]) * TavolsagMalomPekseg[l, p] * Benzinar;
# Adatok
data;
set Mezo := mezo1 mezo2 mezo3 mezo4;
set Malom := malom1 malom2;
set Pekseg := pek1 pek2 pek3;
param Buza :=
mezo1 36526
mezo2 12368
mezo3 25634
mezo4 9999;
param MalomKapacitas :=
malom1 50000
malom2 60000;
param TavolsagMezoMalom : malom1 malom2 :=
mezo1 201 79
mezo2 174 143
mezo3 107 102
mezo4 130 21;
param TavolsagMalomPekseg : pek1 pek2 pek3 :=
malom1 184 98 60
malom2 79 58 159;
param TeherautoKapacitas := 500;
param OrlesArany := 0.9;
param UresFogyasztas := 10;
param ValtozoFogyasztas := 0.006;
param Benzinar := 600;
end;

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Problem: malom
Rows: 9
Columns: 14
Non-zeros: 44
Status: OPTIMAL
Objective: TeljesUzemanyagKoltseg = 9570000 (MINimum)
No. Row name St Activity Lower bound Upper bound Marginal
------ ------------ -- ------------- ------------- ------------- -------------
1 KeszletKorlatozas[mezo1]
B 0 36526
2 KeszletKorlatozas[mezo2]
B 0 12368
3 KeszletKorlatozas[mezo3]
B 0 25634
4 KeszletKorlatozas[mezo4]
B 0 9999
5 MalomKapacitasKorlatozas[malom1]
B 0 50000
6 MalomKapacitasKorlatozas[malom2]
B 0 60000
7 OrlesiAranyKorlatozas[malom1]
B 0 -0
8 OrlesiAranyKorlatozas[malom2]
B 0 -0
9 TeljesUzemanyagKoltseg
B 0
No. Column name St Activity Lower bound Upper bound Marginal
------ ------------ -- ------------- ------------- ------------- -------------
1 SzallitasMezoMalom[mezo1,malom1]
NL 0 0 723.6
2 SzallitasMezoMalom[mezo1,malom2]
NL 0 0 284.4
3 SzallitasMezoMalom[mezo2,malom1]
NL 0 0 626.4
4 SzallitasMezoMalom[mezo2,malom2]
NL 0 0 514.8
5 SzallitasMezoMalom[mezo3,malom1]
NL 0 0 385.2
6 SzallitasMezoMalom[mezo3,malom2]
NL 0 0 367.2
7 SzallitasMezoMalom[mezo4,malom1]
NL 0 0 468
8 SzallitasMezoMalom[mezo4,malom2]
NL 0 0 75.6
9 SzallitasMalomPekseg[malom1,pek1]
NL 0 0 662.4
10 SzallitasMalomPekseg[malom1,pek2]
NL 0 0 352.8
11 SzallitasMalomPekseg[malom1,pek3]
NL 0 0 216
12 SzallitasMalomPekseg[malom2,pek1]
NL 0 0 284.4
13 SzallitasMalomPekseg[malom2,pek2]
NL 0 0 208.8
14 SzallitasMalomPekseg[malom2,pek3]
NL 0 0 572.4
Karush-Kuhn-Tucker optimality conditions:
KKT.PE: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
KKT.PB: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
KKT.DE: max.abs.err = 0.00e+00 on column 0
max.rel.err = 0.00e+00 on column 0
High quality
KKT.DB: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
End of output

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var cs1, binary;
var cs2, binary;
var cs3, binary;
var cs4, binary;
var cs5, binary;
var y1 >= 0, integer;
var y2 >= 0, integer;
var y3 >= 0, integer;
var y4 >= 0, integer;
var y5 >= 0, integer;
var y6 >= 0, integer;
s.t. bcsoki: cs2 + cs4 + cs5 - y1 = 1;
s.t. bnarancs: cs1 + cs4 - y2 = 1;
s.t. bmogyoro: cs1 + cs2 - y3 = 1;
s.t. bvirgacs: cs3 + cs5 - y4 = 1;
s.t. bkinder: cs3 + cs4 - y5 = 1;
s.t. bgumicukor: cs2 + cs3 - y6 = 1;
minimize koltseg: (5*cs1 + cs2*10 + cs3*3 + cs4*4 + cs5*6) + (y1*2 + y2*3 + y3*1 + y4*4 + y5*5 + y6*6);
end;

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Problem: mikulas
Rows: 7
Columns: 11 (11 integer, 5 binary)
Non-zeros: 30
Status: INTEGER OPTIMAL
Objective: koltseg = 18 (MINimum)
No. Row name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 bcsoki 1 1 =
2 bnarancs 1 1 =
3 bmogyoro 1 1 =
4 bvirgacs 1 1 =
5 bkinder 1 1 =
6 bgumicukor 1 1 =
7 koltseg 18
No. Column name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 cs1 * 1 0 1
2 cs2 * 0 0 1
3 cs3 * 1 0 1
4 cs4 * 0 0 1
5 cs5 * 1 0 1
6 y1 * 0 0
7 y2 * 0 0
8 y3 * 0 0
9 y4 * 1 0
10 y5 * 0 0
11 y6 * 0 0
Integer feasibility conditions:
KKT.PE: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
KKT.PB: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
End of output

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var ing >= 0, integer;
var szoknya >= 0, integer;
s.t. anyag: ing*3 + szoknya*4 <= 12;
s.t. ido: ing*5 + szoknya*2 = 10;
s.t. darab: ing + szoknya >= 4;
maximize ruha: ing*4 + szoknya*3;
end;

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Problem: szabo
Rows: 4
Columns: 2 (2 integer, 0 binary)
Non-zeros: 8
Status: INTEGER EMPTY
Objective: ruha = 0 (MAXimum)
No. Row name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 anyag 0 12
2 ido 0 10 =
3 darab 0 4
4 ruha 0
No. Column name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 ing * 0 0
2 szoknya * 0 0
Integer feasibility conditions:
KKT.PE: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
KKT.PB: max.abs.err = 1.00e+01 on row 2
max.rel.err = 9.09e-01 on row 2
SOLUTION IS INFEASIBLE
End of output

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#K<EFBFBD>t f<EFBFBD>le szendvicset k<EFBFBD>sz<EFBFBD>t<EFBFBD>nk
#Szal<EFBFBD>mis szendvics - 3 gramm vaj, 3 karika toj<EFBFBD>s, 2 szelet szal<EFBFBD>mi
#Sonk<EFBFBD>s szendvics - 4 gramm vaj 2 karika toj<EFBFBD>s, 1 szelet sonka
#<EFBFBD>sszesen 100 szelet szal<EFBFBD>mi, 40 szelet sonka, 170 karika toj<EFBFBD>s <EFBFBD>s 220 gramm vaj van. Keny<EFBFBD>r szelet korl<EFBFBD>tlan
#Melyik fajta szendvicsb<EFBFBD>l mennyit kell k<EFBFBD>sz<EFBFBD>teni, ahhoz, hogy a lehet<EFBFBD> legt<EFBFBD>bb szendvicset tudjam elk<EFBFBD>sz<EFBFBD>teni
#Megold<EFBFBD>s:
var sonkas >= 0, integer;
var szalamis >= 0, integer;
s.t. vaj: 3* szalamis + 4* sonkas <= 220;
s.t. tojas: 3* szalamis + 2* sonkas <= 170;
s.t. szalami: 2* szalamis <= 100;
s.t. sonka: 1* sonkas <= 40;
maximize szendvicsekszama: sonkas + szalamis;
end;

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gyakorlatok/szendvicsek.out Normal file
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Problem: szendvicsek
Rows: 5
Columns: 2 (2 integer, 0 binary)
Non-zeros: 8
Status: INTEGER OPTIMAL
Objective: szendvicsekszama = 65 (MAXimum)
No. Row name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 vaj 220 220
2 tojas 170 170
3 szalami 80 100
4 sonka 25 40
5 szendvicsekszama
65
No. Column name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 sonkas * 25 0
2 szalamis * 40 0
Integer feasibility conditions:
KKT.PE: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
KKT.PB: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
End of output

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var eper >= 0, integer;
var spenot >=0, integer;
s.t. ossztabletta: eper + spenot <= 8
s.t. vizsgasiker: eper*7+spenot*10 >=60;
s.t. osszetetel: spenot <= epres;
minimize tabletta: eper*1500 + spenot*2000;
end;

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gyakorlatok/tabletta.mod Normal file
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var eper >=0, integer;
var spenot >=0, integer;
s.t. ossztabletta: eper + spenot <= 8;
s.t. vizsgasiker: eper*7 + spenot*10 >=60;
s.t. osszetetel: spenot <= eper;
minimize tabletta: eper*1500 + spenot*2000;
end;

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Problem: tabletta
Rows: 4
Columns: 2 (2 integer, 0 binary)
Non-zeros: 8
Status: INTEGER OPTIMAL
Objective: tabletta = 13000 (MINimum)
No. Row name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 ossztabletta 8 8
2 vizsgasiker 62 60
3 osszetetel -4 -0
4 tabletta 13000
No. Column name Activity Lower bound Upper bound
------ ------------ ------------- ------------- -------------
1 eper * 6 0
2 spenot * 2 0
Integer feasibility conditions:
KKT.PE: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
KKT.PB: max.abs.err = 0.00e+00 on row 0
max.rel.err = 0.00e+00 on row 0
High quality
End of output