1 | # A TRANSPORTATION PROBLEM |
---|
2 | # |
---|
3 | # This problem finds a least cost shipping schedule that meets |
---|
4 | # requirements at markets and supplies at factories. |
---|
5 | # |
---|
6 | # References: |
---|
7 | # Dantzig G B, "Linear Programming and Extensions." |
---|
8 | # Princeton University Press, Princeton, New Jersey, 1963, |
---|
9 | # Chapter 3-3. |
---|
10 | |
---|
11 | set I; |
---|
12 | /* canning plants */ |
---|
13 | |
---|
14 | set J; |
---|
15 | /* markets */ |
---|
16 | |
---|
17 | param a{i in I}; |
---|
18 | /* capacity of plant i in cases */ |
---|
19 | |
---|
20 | param b{j in J}; |
---|
21 | /* demand at market j in cases */ |
---|
22 | |
---|
23 | param d{i in I, j in J}; |
---|
24 | /* distance in thousands of miles */ |
---|
25 | |
---|
26 | param f; |
---|
27 | /* freight in dollars per case per thousand miles */ |
---|
28 | |
---|
29 | param c{i in I, j in J} := f * d[i,j] / 1000; |
---|
30 | /* transport cost in thousands of dollars per case */ |
---|
31 | |
---|
32 | var x{i in I, j in J} >= 0; |
---|
33 | /* shipment quantities in cases */ |
---|
34 | |
---|
35 | minimize cost: sum{i in I, j in J} c[i,j] * x[i,j]; |
---|
36 | /* total transportation costs in thousands of dollars */ |
---|
37 | |
---|
38 | s.t. supply{i in I}: sum{j in J} x[i,j] <= a[i]; |
---|
39 | /* observe supply limit at plant i */ |
---|
40 | |
---|
41 | s.t. demand{j in J}: sum{i in I} x[i,j] >= b[j]; |
---|
42 | /* satisfy demand at market j */ |
---|
43 | |
---|
44 | data; |
---|
45 | |
---|
46 | set I := Seattle San-Diego; |
---|
47 | |
---|
48 | set J := New-York Chicago Topeka; |
---|
49 | |
---|
50 | param a := Seattle 350 |
---|
51 | San-Diego 600; |
---|
52 | |
---|
53 | param b := New-York 325 |
---|
54 | Chicago 300 |
---|
55 | Topeka 275; |
---|
56 | |
---|
57 | param d : New-York Chicago Topeka := |
---|
58 | Seattle 2.5 1.7 1.8 |
---|
59 | San-Diego 2.5 1.8 1.4 ; |
---|
60 | |
---|
61 | param f := 90; |
---|
62 | |
---|
63 | end; |
---|