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Linear Programming code |
Max profit
@LP : 2-14
2 3 NO MAX
ALPHA 4 BETA-5 CONST TYPE R H S RANGE
OBJ COEFF 1200 1800 XXXX XXXX XXXX
MIN-PROD 1 0 >= 10 .
MIN-PROD2 0 1 >= 15 .
LABORHRS 20 25 = 800 .
VARBL TYPE POS POS XXXX XXXX XXXX
LOWR BOUND . . XXXX XXXX XXXX
UPPR BOUND . . XXXX XXXX XXXX
INIT SOLN 0 0 XXXX XXXX XXXX
Assembly line balancing
@ALB : BAR-B-Q Grill Company
21 3 1.000000
TASK NUMBR TASK TIME PRED 1 PRED 2 PRED 3
CHECK PTS 1 0.630000 . . .
TOP>SIDE 2 1.000000 1 . .
HOLDER 1 3 0.330000 2 . .
HOLDER 2 4 0.330000 2 . .
INSP HOOD 5 0.080000 3 4 .
MOUNT BRK 6 1.000000 1 . .
RACK>BOWL 7 0.080000 6 . .
INSP BOWL 8 0.050000 7 . .
LEGS>TOP 9 1.500000 1 . .
BRACE LEGS 10 2.000000 9 . .
WHEEL 1 11 0.500000 10 . .
WHEEL 2 12 0.500000 10 . .
WHEEL 3 13 0.500000 10 . .
INSP BASE 14 0.170000 11 12 13
PRONGS 15 0.200000 1 . .
MOTOR 16 0.050000 15 . .
INSP ROTIS 17 0.050000 16 . .
HOOD>BOWL 18 1.000000 5 8 .
BASE>BOWL 19 2.000000 14 18 .
ROTIS>HOLD 20 0.050000 19 . .
FINAL INSP 21 0.500000 20 . .
18 .
ROTIS>HOLD 20 0.05000000 . 19 .
FINAL INSP 21 0.50000000 20 . .
19 .
FINAL INSP 21 0.50000000 20 . .
Linear programming.
@LP : LAWSON-BLENDING2
4 4 NO MIN
1REGULAR 1PREMIUM 2REGULAR 2PREMIUM CONST TYPE R H S RANGE
OBJ COEFF 30 30 34.8 34.8 XXXX XXXX XXXX
DEMAND-REG 1 0 1 0 >= 25000 .
DEMAND-PRE 0 1 0 1 >= 32000 .
SUBSTANCEA -0.1 0 0.15 0 >= 0 .
SUBSTANCEB 0 0.05 0 -0.25 <= 0 .
VARBL TYPE POS POS POS POS XXXX XXXX XXXX
LOWR BOUND . . . . XXXX XXXX XXXX
UPPR BOUND . . . . XXXX XXXX XXXX
INIT SOLN 0 0 0 0 XXXX XXXX XXXX
@LP : LAWSON-BLENDIND
3 5 NO MIN
GRAIN-A GRAIN-B GRAIN-C CONST TYPE R H S RANGE
OBJ COEFF 0.33 0.47 0.38 XXXX XXXX XXXX
PROTEIN
22 28 21 >= 3 .
RIBOFLAVIN
16 14 25 >= 2 .
PHOSPHORUS
8 7 9 >= 1 .
MAGNESIUM
5 0 6 >= 0.425 .
TOTAL-MIX
1 1 1 = 0.125 .
VARBL TYPE POS POS POS XXXX XXXX XXXX
LOWR BOUND . . . XXXX XXXX XXXX
UPPR BOUND . . . XXXX XXXX XXXX
INIT SOLN 0 0 0 XXXX XXXX XXXX
@MRP : BLUE RIDGE FURNITURE COMPANY
12 5
ITEM ID ITEM TYPE DESC 1 Q/ASSY 1 DESC 2 Q/ASSY 2 DESC 3
Q/ASSY 3 DESC 4 Q/ASSY 4 DESC 5 Q/ASSY 5
STOOL-STD 1 MAT 11 4 12 4 21 1 99 0.5 . .
STOOL-DLX 2 MAT 11 4 12 4 13 1 14 1 99 0.7
LEG 11 MAT . . . . . . . . . .
BRACE 12 MAT . . . . . . . . . .
SEAT ASSY 13 MAT 21 1 22 1 23 1 99 0.2 199 1
BACK ASSY 14 MAT 24 1 22 1 23 1 99 0.2 199 1
SEAT 21 MAT . . . . . . . . . .
PAD 22 MAT . . . . . . . . . .
FABRIC 23 MAT . . . . . . . . . .
BACK 24 MAT . . . . . . . . . .
LABOR 99 CAP . . . . . . . . . .
SETUP STPL 199 SET 99 0.2 . . . . . . . .
@LP : LAWSON MEDIA
4 7 NO MAX
TV NEWSPAPER RADIO-1 RADIO-2 CONST TYPE R H S RANGE
OBJ COEFF 5000 8500 2400 2800 XXXX XXXX XXXX
MAX-TV 1 0 0 0 <= 12 .
MAX-PAPER 0 1 0 0 <= 5 .
MAX-RADIO1 0 0 1 0 <= 25 .
MAX-RADIO2 0 0 0 1 <= 20 .
MAX-BUDGET 800 925 290 380 <= 8000 .
MIN-RADIO 0 0 1 1 >= 5 .
MAX-RADIO$ 0 0 290 380 <= 1800 .
VARBL TYPE POS POS POS POS XXXX XXXX XXXX
LOWR BOUND . . . . XXXX XXXX XXXX
UPPR BOUND . . . . XXXX XXXX XXXX
INIT SOLN 0 0 0 0 XXXX XXXX XXXX
@MRP : BLUE RIDGE FURNITURE COMPANY
10 2 2 25
ITEM ID SAFE STOCK ON HAND PAST DUE RECEIPT 1 RECEIPT 2 FPO ->
FPO 1 FPO 2
STOOL-STD 1 50 53 0 0 0 XXXX 0 0
STOOL-DLX 2 25 36 0 0 0 XXXX 0 0
LEG 11 0 112 0 0 0 XXXX 0 0
BRACE 12 0 36 0 500 0 XXXX 0 0
SEAT ASSY 13 0 1 0 0 0 XXXX 0 100
BACK ASSY 14 0 0 0 0 0 XXXX 0 100
SEAT 21 0 45 0 0 0 XXXX 0 0
PAD 22 0 22 0 50 0 XXXX 0 0
FABRIC 23 100 9 0 0 0 XXXX 0 0
BACK 24 0 14 0 0 0 XXXX 0 0
@PM : PROBABILISTIC ACTIVITY TIMES
13 PROB ARC 0
SYMBOL OPTIMISTIC LIKELY PESIMISTIC START NODE END NODE
ACT 1 MGR 3 3 3 1 3
ACT 2 STDY 5.6 6 6.4 2 4
ACT 3 PER1 5 5 5 3 6
ACT 4 D1 0 0 0 3 5
ACT 5 D2 0 0 0 4 6
ACT 6 D3 0 0 0 4 5
ACT 7 BLDG 2.4 2.6 5.2 4 7
ACT 8 PICK 2 3.2 3.2 5 8
ACT 9 PER2 3 3 3 6 9
ACT 10 FURN 4 4.6 7.6 7 9
ACT 11 DLRS 2.6 4.2 4.6 8 9
ACT 12 STOK 2 3 4 9 10
ACT 13 ADV 2 2 2 8 11
Scheduling Baseball Pitchers.
@LP : LAWSON3-5
16 8 NO MAX
X11 X12 X13 X14 X21 X22 X23
X24 X31 X32 X33 X34 X41 X42
X43 X44 CONST TYPE R H S RANGE
OBJ COEFF 0.6 0.8 0.5 0.4 0.7 0.4 0.8 0.3 0.9 0.8 0.7 0.8 0.5 0.3 0.4 0.2
XXXX XXXX XXXX
JONES 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 = 1 .
BAKER 0 0 0 0 1 1 1 1 0 0 0 0 0 0 0 0 = 1 .
PARKER 0 0 0 0 0 0 0 0 1 1 1 1 0 0 0 0 = 1 .
WILSON 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 = 1 .
DESMOINES 1 0 0 0 1 0 0 0 1 0 0 0 1 0 0 0 = 1 .
DAVENPORT 0 1 0 0 0 1 0 0 0 1 0 0 0 1 0 0 = 1 .
OMAHA 0 0 1 0 0 0 1 0 0 0 1 0 0 0 1 0 = 1 .
PEORIA 0 0 0 1 0 0 0 1 0 0 0 1 0 0 0 1 = 1 .
VARBL TYPE POS POS POS POS POS POS POS POS POS POS POS POS POS
POS POS POS XXXX XXXX XXXX
LOWR BOUND . . . . . . . . . . . . . . . . XXXX XXXX XXXX
UPPR BOUND . . . . . . . . . . . . . . . . XXXX XXXX XXXX
INIT SOLN 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 XXXX XXXX XXXX
Assignment programming. This case police detectives.
@ASN : LAWSON-6-27
5 5 MIN
CASE-A CASE-B CASE-C CASE-D CASE-E
SQUAD-1 14 7 3 7 27
SQUAD-2 20 7 12 6 30
SQUAD-3 10 3 4 5 21
SQUAD-4 8 12 7 12 21
SQUAD-5 13 25 24 26 8
Teachers.
@ASN : LAWSON6-28
4 4 MAX
STATS MGMT. FINANCE ECONOMICS
ANDERSON 90 65 95 40
SWEENY 70 60 80 75
WILLIAMS 85 40 80 60
MCKINNEY 55 80 65 55
Minimize cost while assembling parts at the optimal factory location.
@ASN : LAWSON6-33
7 8 MIN
PLANT-1 PLANT-2 PLANT-3 PLANT-4 PLANT-5 PLANT-6 PLANT-7
PLANT-8
PART-C53 100 12 13 11 10 6 16 12
PART-C81 5 6 4 8 4 9 6 6
PART-D5 32 40 31 30 42 35 36 49
PART-D44 17 14 19 15 10 16 19 12
PART-E2 6 7 10 5 8 10 11 5
PART-E35 8 10 12 8 9 10 9 6
PART-G99 55 62 61 70 62 63 65 59
Scheduling NASA personnel on the shuttle.
@ASN : LAWSON6-35
10 10 MAX
JAN-12 JAN-27 FEB-5 FEB-26 MAR-26 APR-12 MAY-1
JUN-9 AUG-20 SEPT-19
VINCZE 9 7 2 1 10 9 8 9 2 6
VEIT 8 8 3 4 7 9 7 7 4 4
ANDERSON 2 1 10 10 1 4 7 6 6 7
HERBERT 4 4 10 9 9 9 1 2 3 4
SCHATZ 10 10 9 9 8 9 1 1 1 1
PLANE 1 3 5 7 9 7 10 10 9 2
CERTO 9 9 8 8 9 1 1 2 2 9
MOSES 3 2 7 6 4 3 9 7 7 9
BRANDON 5 4 5 9 10 10 5 4 9 8
DRTINA 10 10 9 7 6 7 5 4 8 8
@LP : LAWSON-PRODUCTION
4 11 NO MAX
ALL-SILK ALL-POLY BLEND1 BLEND2 CONST TYPE R H S RANGE
OBJ COEFF 4.08 3.07 3.56 4 XXXX XXXX XXXX
SILK-AMT 0.125 0 0 0 <= 800 .
POLY-AMT 0 0.08 0.05 0.03 <= 3000 .
BLEND-AMT 0 0 0.05 0.07 <= 1600 .
SILK-MIN 1 0 0 0 >= 6000 .
SILK-MAX 1 0 0 0 <= 7000 .
POLY-MIN 0 1 0 0 >= 10000 .
POLY-MAX 0 1 0 0 <= 14000 .
BLEND1MIN 0 0 1 0 >= 13000 .
BLEND1MAX 0 0 1 0 <= 16000 .
BLEND2MIN 0 0 0 1 >= 6000 .
BLEND2MAX 0 0 0 1 <= 8500 .
VARBL TYPE POS POS POS POS XXXX XXXX XXXX
LOWR BOUND . . . . XXXX XXXX XXXX
UPPR BOUND . . . . XXXX XXXX XXXX
INIT SOLN 0 0 0 0 XXXX XXXX XXXX
@LP : LAWSON-SHIPPING
6 5 NO MIN
NEWO-NYORK NEWO-CHICA NEWO-LA OMAHA-NYRK OMAHA-CHIC OMAHO-LA CONST TYPE
R H S RANGE
OBJ COEFF 2 3 5 3 1 4 XXXX XXXX XXXX
DEMAND-NY 1 0 0 1 0 0 = 10000 .
DEMAND-CHI 0 1 0 0 1 0 = 8000 .
DEMAND-LA 0 0 1 0 0 1 = 15000 .
SUPPLY-NOL 1 1 1 0 0 0 <= 20000 .
SUPPLY-OMA 0 0 0 1 1 1 <= 15000 .
VARBL TYPE POS POS POS POS POS POS XXXX XXXX XXXX
LOWR BOUND . . . . . . XXXX XXXX XXXX
UPPR BOUND . . . . . . XXXX XXXX XXXX
INIT SOLN 0 0 0 0 0 0 XXXX XXXX XXXX
@TR : SAMPLE TRANSPORTATION PROBLEM: CAPACITATED ROUTES
CAP 2 3 MIN NONE
TERMINAL 1 TERMINAL 2 TERMINAL 3 DUMMY SUPPLY
REFINERY 1 2 2.8 3.8 | 50
REFINERY 2 3 4 4.2 | 50
DUMMY ---- ---- ---- ---- ----
DEMAND 25 45 10 | XXXX
CAP 1 . 30 . | XXXX
CAP 2 . . 5 | XXXX
·
0
0 0 * *
|
BACK TO 100 examples in Business, Operations and
Engineering. |
|
Do it once, do it right, and do it now.
|
|
Back to Lawson Computing Homepage
|
Apply as needed,
when needed. |
