This repository has been archived by the owner on Aug 15, 2024. It is now read-only.
-
Notifications
You must be signed in to change notification settings - Fork 10
/
Copy pathlap.cpp
executable file
·369 lines (326 loc) · 10.4 KB
/
lap.cpp
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
/************************************************************************
*
* lap.cpp
version 1.0 - 4 September 1996
author: Roy Jonker @ MagicLogic Optimization Inc.
e-mail: [email protected]
Code for Linear Assignment Problem, according to
"A Shortest Augmenting Path Algorithm for Dense and Sparse Linear
Assignment Problems," Computing 38, 325-340, 1987
by
R. Jonker and A. Volgenant, University of Amsterdam.
*
CHANGED 2004-08-13 by Harold Cooper ([email protected]) for the pyLAPJV Python module:
-- commented out system.h and checklap()
*
*************************************************************************/
//#include "system.h"
#include "gnrl.h"
#include "lap.h"
cost lap(int dim,
cost **assigncost,
col *rowsol,
row *colsol,
cost *u,
cost *v)
// input:
// dim - problem size
// assigncost - cost matrix
// output:
// rowsol - column assigned to row in solution
// colsol - row assigned to column in solution
// u - dual variables, row reduction numbers
// v - dual variables, column reduction numbers
{
boolean unassignedfound;
row i, imin, numfree = 0, prvnumfree, f, i0, k, freerow, *pred, *free;
col j, j1, j2, endofpath, last, low, up, *collist, *matches;
cost min, h, umin, usubmin, v2, *d;
free = new row[dim]; // list of unassigned rows.
collist = new col[dim]; // list of columns to be scanned in various ways.
matches = new col[dim]; // counts how many times a row could be assigned.
d = new cost[dim]; // 'cost-distance' in augmenting path calculation.
pred = new row[dim]; // row-predecessor of column in augmenting/alternating path.
// init how many times a row will be assigned in the column reduction.
for (i = 0; i < dim; i++)
matches[i] = 0;
// COLUMN REDUCTION
for (j = dim-1; j >= 0; j--) // reverse order gives better results.
{
// find minimum cost over rows.
min = assigncost[0][j];
imin = 0;
for (i = 1; i < dim; i++)
if (assigncost[i][j] < min)
{
min = assigncost[i][j];
imin = i;
}
v[j] = min;
if (++matches[imin] == 1)
{
// init assignment if minimum row assigned for first time.
rowsol[imin] = j;
colsol[j] = imin;
}
else
colsol[j] = -1; // row already assigned, column not assigned.
}
// REDUCTION TRANSFER
for (i = 0; i < dim; i++)
if (matches[i] == 0) // fill list of unassigned 'free' rows.
free[numfree++] = i;
else
if (matches[i] == 1) // transfer reduction from rows that are assigned once.
{
j1 = rowsol[i];
min = BIG;
for (j = 0; j < dim; j++)
if (j != j1)
if (assigncost[i][j] - v[j] < min)
min = assigncost[i][j] - v[j];
v[j1] = v[j1] - min;
}
// AUGMENTING ROW REDUCTION
int loopcnt = 0; // do-loop to be done twice.
do
{
loopcnt++;
// scan all free rows.
// in some cases, a free row may be replaced with another one to be scanned next.
k = 0;
prvnumfree = numfree;
numfree = 0; // start list of rows still free after augmenting row reduction.
while (k < prvnumfree)
{
i = free[k];
k++;
// find minimum and second minimum reduced cost over columns.
umin = assigncost[i][0] - v[0];
j1 = 0;
usubmin = BIG;
for (j = 1; j < dim; j++)
{
h = assigncost[i][j] - v[j];
if (h < usubmin)
if (h >= umin)
{
usubmin = h;
j2 = j;
}
else
{
usubmin = umin;
umin = h;
j2 = j1;
j1 = j;
}
}
i0 = colsol[j1];
if (umin < usubmin)
// change the reduction of the minimum column to increase the minimum
// reduced cost in the row to the subminimum.
v[j1] = v[j1] - (usubmin - umin);
else // minimum and subminimum equal.
if (i0 >= 0) // minimum column j1 is assigned.
{
// swap columns j1 and j2, as j2 may be unassigned.
j1 = j2;
i0 = colsol[j2];
}
// (re-)assign i to j1, possibly de-assigning an i0.
rowsol[i] = j1;
colsol[j1] = i;
if (i0 >= 0) // minimum column j1 assigned earlier.
if (umin < usubmin)
// put in current k, and go back to that k.
// continue augmenting path i - j1 with i0.
free[--k] = i0;
else
// no further augmenting reduction possible.
// store i0 in list of free rows for next phase.
free[numfree++] = i0;
}
}
while (loopcnt < 2); // repeat once.
// AUGMENT SOLUTION for each free row.
for (f = 0; f < numfree; f++)
{
freerow = free[f]; // start row of augmenting path.
// Dijkstra shortest path algorithm.
// runs until unassigned column added to shortest path tree.
for (j = 0; j < dim; j++)
{
d[j] = assigncost[freerow][j] - v[j];
pred[j] = freerow;
collist[j] = j; // init column list.
}
low = 0; // columns in 0..low-1 are ready, now none.
up = 0; // columns in low..up-1 are to be scanned for current minimum, now none.
// columns in up..dim-1 are to be considered later to find new minimum,
// at this stage the list simply contains all columns
unassignedfound = FALSE;
do
{
if (up == low) // no more columns to be scanned for current minimum.
{
last = low - 1;
// scan columns for up..dim-1 to find all indices for which new minimum occurs.
// store these indices between low..up-1 (increasing up).
min = d[collist[up++]];
for (k = up; k < dim; k++)
{
j = collist[k];
h = d[j];
if (h <= min)
{
if (h < min) // new minimum.
{
up = low; // restart list at index low.
min = h;
}
// new index with same minimum, put on undex up, and extend list.
collist[k] = collist[up];
collist[up++] = j;
}
}
// check if any of the minimum columns happens to be unassigned.
// if so, we have an augmenting path right away.
for (k = low; k < up; k++)
if (colsol[collist[k]] < 0)
{
endofpath = collist[k];
unassignedfound = TRUE;
break;
}
}
if (!unassignedfound)
{
// update 'distances' between freerow and all unscanned columns, via next scanned column.
j1 = collist[low];
low++;
i = colsol[j1];
h = assigncost[i][j1] - v[j1] - min;
for (k = up; k < dim; k++)
{
j = collist[k];
v2 = assigncost[i][j] - v[j] - h;
if (v2 < d[j])
{
pred[j] = i;
if (v2 == min) // new column found at same minimum value
if (colsol[j] < 0)
{
// if unassigned, shortest augmenting path is complete.
endofpath = j;
unassignedfound = TRUE;
break;
}
// else add to list to be scanned right away.
else
{
collist[k] = collist[up];
collist[up++] = j;
}
d[j] = v2;
}
}
}
}
while (!unassignedfound);
// update column prices.
for (k = 0; k <= last; k++)
{
j1 = collist[k];
v[j1] = v[j1] + d[j1] - min;
}
// reset row and column assignments along the alternating path.
do
{
i = pred[endofpath];
colsol[endofpath] = i;
j1 = endofpath;
endofpath = rowsol[i];
rowsol[i] = j1;
}
while (i != freerow);
}
// calculate optimal cost.
cost lapcost = 0;
for (i = 0; i < dim; i++)
{
j = rowsol[i];
u[i] = assigncost[i][j] - v[j];
lapcost = lapcost + assigncost[i][j];
}
// free reserved memory.
delete[] pred;
delete[] free;
delete[] collist;
delete[] matches;
delete[] d;
return lapcost;
}
//UNUSED by pyLAPJV, so commented out:
/*void checklap(int dim, cost **assigncost,
col *rowsol, row *colsol, cost *u, cost *v)
{
row i;
col j;
cost lapcost = 0, redcost = 0;
boolean *matched;
char wait;
matched = new boolean[dim];
for (i = 0; i < dim; i++)
for (j = 0; j < dim; j++)
if ((redcost = assigncost[i][j] - u[i] - v[j]) < 0)
{
printf("\n");
printf("negative reduced cost i %d j %d redcost %d\n", i, j, redcost);
printf("\n\ndim %5d - press key\n", dim);
scanf("%d", &wait);
break;
}
for (i = 0; i < dim; i++)
if ((redcost = assigncost[i][rowsol[i]] - u[i] - v[rowsol[i]]) != 0)
{
printf("\n");
printf("non-null reduced cost i %d soli %d redcost %d\n", i, rowsol[i], redcost);
printf("\n\ndim %5d - press key\n", dim);
scanf("%d", &wait);
break;
}
for (j = 0; j < dim; j++)
matched[j] = FALSE;
for (i = 0; i < dim; i++)
if (matched[rowsol[i]])
{
printf("\n");
printf("column matched more than once - i %d soli %d\n", i, rowsol[i]);
printf("\n\ndim %5d - press key\n", dim);
scanf("%d", &wait);
break;
}
else
matched[rowsol[i]] = TRUE;
for (i = 0; i < dim; i++)
if (colsol[rowsol[i]] != i)
{
printf("\n");
printf("error in row solution i %d soli %d solsoli %d\n", i, rowsol[i], colsol[rowsol[i]]);
printf("\n\ndim %5d - press key\n", dim);
scanf("%d", &wait);
break;
}
for (j = 0; j < dim; j++)
if (rowsol[colsol[j]] != j)
{
printf("\n");
printf("error in col solution j %d solj %d solsolj %d\n", j, colsol[j], rowsol[colsol[j]]);
printf("\n\ndim %5d - press key\n", dim);
scanf("%d", &wait);
break;
}
delete[] matched;
return;
}*/