COIN-OR::LEMON - Graph Library

source: lemon-project-template-glpk/deps/glpk/examples/gap.mod @ 9:33de93886c88

subpack-glpk
Last change on this file since 9:33de93886c88 was 9:33de93886c88, checked in by Alpar Juttner <alpar@…>, 13 years ago

Import GLPK 4.47

File size: 2.5 KB
Line 
1/* GAP, Generalized Assignment Problem */
2
3/* Written in GNU MathProg by Andrew Makhorin <mao@gnu.org> */
4
5/* The Generalized Assignment Problem (GAP) is to assign a set of jobs
6   to a set of agents subject to the constraints that each job must be
7   assigned exactly to one agent and the total resources consumed by all
8   jobs assigned to an agent must not exceed the agent's capacity. */
9
10param m, integer, > 0;
11/* number of agents */
12
13param n, integer, > 0;
14/* number of jobs */
15
16set I := 1..m;
17/* set of agents */
18
19set J := 1..n;
20/* set of jobs */
21
22param a{i in I, j in J}, >= 0;
23/* resource consumed in allocating job j to agent i */
24
25param b{i in I}, >= 0;
26/* resource capacity of agent i */
27
28param c{i in I, j in J}, >= 0;
29/* cost of allocating job j to agent i */
30
31var x{i in I, j in J}, binary;
32/* x[i,j] = 1 means job j is assigned to agent i */
33
34s.t. one{j in J}: sum{i in I} x[i,j] = 1;
35/* job j must be assigned exactly to one agent */
36
37s.t. lim{i in I}: sum{j in J} a[i,j] * x[i,j] <= b[i];
38/* total amount of resources consumed by all jobs assigned to agent i
39   must not exceed the agent's capacity */
40
41minimize obj: sum{i in I, j in J} c[i,j] * x[i,j];
42/* the objective is to find cheapest assignment (note that gap can also
43   be formulated as maximization problem) */
44
45data;
46
47/* These data correspond to the instance c515-1 (gap1) from:
48
49   I.H. Osman, "Heuristics for the Generalised Assignment Problem:
50   Simulated Annealing and Tabu Search Approaches", OR Spektrum, Volume
51   17, 211-225, 1995
52
53   D. Cattrysse, M. Salomon and L.N. Van Wassenhove, "A set partitioning
54   heuristic for the generalized assignment problem", European Journal
55   of Operational Research, Volume 72, 167-174, 1994 */
56
57/* The optimal solution is 261 (minimization) or 336 (maximization) */
58
59param m := 5;
60
61param n := 15;
62
63param a :  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 :=
64      1    8 15 14 23  8 16  8 25  9 17 25 15 10  8 24
65      2   15  7 23 22 11 11 12 10 17 16  7 16 10 18 22
66      3   21 20  6 22 24 10 24  9 21 14 11 14 11 19 16
67      4   20 11  8 14  9  5  6 19 19  7  6  6 13  9 18
68      5    8 13 13 13 10 20 25 16 16 17 10 10  5 12 23 ;
69
70param b := 1 36, 2 34, 3 38, 4 27, 5 33;
71
72param c :  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 :=
73      1   17 21 22 18 24 15 20 18 19 18 16 22 24 24 16
74      2   23 16 21 16 17 16 19 25 18 21 17 15 25 17 24
75      3   16 20 16 25 24 16 17 19 19 18 20 16 17 21 24
76      4   19 19 22 22 20 16 19 17 21 19 25 23 25 25 25
77      5   18 19 15 15 21 25 16 16 23 15 22 17 19 22 24 ;
78
79end;
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